Mehmet Ali Ilgin
email: mehmetali.ilgin@cbu.edu.tr

Surendra M Gupta
email: gupta@neu.edu

Olga Battaïa
email: battaia@emse.fr

Use of MCDM techniques in environmentally conscious manufacturing and product recovery: State of the art

Keywords:

Increasing environmental awareness of customers and stricter environmental regulations by local governments force manufacturers to invest in environmentally conscious manufacturing which involves the application of green principles to all phases of a product's life cycle from conceptual design to final delivery to consumers, and ultimately to the end of life (EOL) disposal. They also setup facilities for product recovery which is the recovery of materials and components from returned or EOL products via disassembly, recycling and remanufacturing. To address these new issues efficiently, multi criteria decision making (MCDM) techniques are used in order to evaluate the economic and environmental indicators. This paper presents over 190 MCDM studies in environmentally conscious manufacturing and product recovery (ECMPRO) by classifying them into three major categories. Insights from the review and future research directions conclude the paper.

Introduction

Substantial improvements in the efficiency of the resource use in manufacturing and reduction of the wastes and emissions generated are required in order to not compromise the health and life standards of future generations. As a response to this societal challenge, stricter environmental regulations and new customer requirements oblige firms to invest in environmentally conscious manufacturing which involves the evaluation of environmental performances of all phases in a product's life cycle (i.e., from material selection to end of life processing option). Due to its social, environmental and economic benefits, product recovery through reverse supply chains is also gaining more and more industrial interest [START_REF] Ilgin | Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art[END_REF][START_REF] Bentaha | Dealing with uncertainty in disassembly line design[END_REF]. Product recovery preserves resources by reducing the consumption of verging raw materials, water and energy. In addition, this process plays a key role in minimizing the amount of waste sent to landfills and diminishing air and water pollution [START_REF] Bentaha | Disassembly line balancing and sequencing under uncertainty[END_REF][START_REF] Bentaha | Lagrangian relaxation for stochastic disassembly line balancing problem[END_REF]. Through recycling, remanufacturing and reuse, product recovery aims to retrieve valuable parts and materials from discarded or end of life (EOL) products.

It had come naturally to firms to evaluate the economic and environmental benefits of such initiatives. Since different kinds of indicators have to be compared in this case, the multi criteria decision making (MCDM) techniques appeared to be the appropriate tools to use. This review presents an analysis of the application of different MCDM techniques in order to help the decision makers implement environmentally conscious manufacturing principles or to engage them in product recovery activities. Over 190 scientific articles published between 1996 and 2014 are concerned by this study.

Fig. 1 presents a global view of a closed-loop supply chain (CLSC). The analysis of the academic literature showed that the topics most addressed with MCDM are green supplier selection and evaluation, disassembly planning, reverse logistics and CLSC design, etc. This is highlighted in Fig. 1 and detailed in Fig. 2 and Table 1.

It was shown in several studies that disassembly is a critical operation in product recovery process since all product disposal options (e.g., recycling, remanufacturing) require the disassembly of EOL products at some level [START_REF] Tang | Disassembly modeling, planning, and application[END_REF][START_REF] Bentaha | An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times[END_REF][START_REF] Bentaha | A sample average approximation method for disassembly line balancing problem under uncertainty[END_REF]. Significant improvements can be achieved in the profitability of product recovery options by effectively planning disassembly process. One of the important disassembly planning problems is the disassembly to order problem which involves the determination of the number of EOL products to process to fulfill a certain demand for products, parts and/or materials under a variety of objectives and constraints.

The MCDM techniques are used both for evaluation and design problems, the major distinction between them is based on whether the solutions/alternatives are explicitly (evaluation problems) or implicitly (design problems) defined. Another criterion of the classification of MCDM techniques is the intervention of the decision maker which can be required a priori (given goals, weights for the objectives), interactive or a posteriori (sorting of given solutions). Based on these observations, the rest of the article is organized in the following way. First, the techniques that are used for searching for new solutions under consideration of multiple optimization objectives are presented in Section 2. This category includes such well known techniques as goal programming and physical programming but also the heuristics and metaheuristics. Section 3 overviews the techniques used for the classification of feasible solutions and Pareto-based ranking. Section 4 overviews the studies implementing both optimization and classification techniques. Finally, concluding remarks are given in Section 5.

Multi-objective optimization techniques

These techniques aim at achieving the optimal or aspired goals by considering the various interactions within the given constraints [START_REF] Tzeng | Multiple attribute decision making: methods and applications[END_REF].

Multi-objective linear and non-linear programming

Wang et al. [START_REF] Wang | A multi-objective optimization for green supply chain network design[END_REF] develop a multi-objective mixed-integer programming formulation for a green supply chain network design problem by considering the trade-off between the total cost and the environment influence. They apply the normalized normal constraint method to solve the multi-objective model. Pishvaee and Razmi [START_REF] Pishvaee | Environmental supply chain network design using multi-objective fuzzy mathematical programming[END_REF] design an environmental supply chain under uncertainty using multi-objective fuzzy mathematical programming. There are two objectives (viz., minimizing the total cost and minimizing the total environmental impact) and the multiobjective programming model is solved by using -constraint method. Ramezani et al. [START_REF] Ramezani | A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level[END_REF] present a stochastic multiobjective model for the design of a forward/reverse supply chain network with the goals of maximization of profit, maximization of responsiveness and minimization of defective parts from suppliers.

-Constraint method is used to determine a set of Pareto-optimal supply chain configuration. Özkır and Bas ¸lıgil [START_REF] Özkır | Multi-objective optimization of closed-loop supply chains in uncertain environment[END_REF] propose a fuzzy multi-objective optimization model for the design of a closed-loop supply chain network by considering three objectives: maximizing satisfaction level of trade, maximizing satisfaction degrees of Fig. 2. Main decision and optimization problems addressed in ECMPRO.

Table 1

Classification of references based on ECMPRO issues.

Issue References

Disassembly planning Gupta and Taleb [START_REF] Gupta | An algorithm to disassemble multiple product structures with multiple occurrence of parts[END_REF]; Taleb and Gupta [START_REF] Taleb | Disassembly of multiple product structures[END_REF]; Zeid et al. [START_REF] Zeid | A case-based reasoning approach to planning for disassembly[END_REF]; Kongar and Gupta [START_REF] Kongar | A goal programming approach to the remanufacturing supply chain model[END_REF]; Gupta and Veerakamolmal [START_REF] Gupta | A case-based reasoning approach for optimal planning of multi-product/multi-manufacturer disassembly processes[END_REF]; Veerakamolmal and Gupta [START_REF] Veerakamolmal | A case-based reasoning approach for automating disassembly process planning[END_REF]; Kongar et al. [START_REF] Kongar | A fuzzy goal programming approach to disassembly planning[END_REF]; Lambert and Gupta [START_REF] Lambert | Disassembly modeling for assembly, maintenance, reuse, and recycling[END_REF]; Imtanavanich and Gupta [START_REF] Imtanavanich | Weighted fuzzy goal programming approach for a disassembly-to-order system[END_REF][START_REF] Imtanavanich | Calculating disassembly yields in a multicriteria decision-making environment for a disassembly-to-order system[END_REF][START_REF] Imtanavanich | Evolutionary computation with linear physical programming for solving a disassembly-to-order system[END_REF][START_REF] Imtanavanich | Linear physical programming approach for a disassembly-to-order system under stochastic yields and product's deterioration[END_REF][START_REF] Imtanavanich | Solving a disassembly-to-order system by using genetic algorithm and weighted fuzzy goal programming[END_REF];

McGovern and Gupta [START_REF] Mcgovern | Ant colony optimization for disassembly sequencing with multiple objectives[END_REF]; Langella [START_REF] Langella | Heuristics for demand-driven disassembly planning[END_REF]; McGovern and Gupta [START_REF] Mcgovern | A balancing method and genetic algorithm for disassembly line balancing[END_REF]; Agrawal and Tiwari [START_REF] Agrawal | A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem[END_REF]; McGovern and Gupta [START_REF] Mcgovern | Lexicographic goal programming and assessment tools for a combinatorial production problem[END_REF]; Lu et al. [START_REF] Lu | A multi-objective disassembly planning approach with ant colony optimization algorithm[END_REF]; Kongar and Gupta [START_REF] Kongar | Solving the disassembly-to-order problem using linear physical programming[END_REF]; Xanthopoulos and Iakovou [START_REF] Xanthopoulos | On the optimal design of the disassembly and recovery processes[END_REF]; Ding et al. [START_REF] Ding | A new multi-objective ant colony algorithm for solving the disassembly line balancing problem[END_REF][START_REF] Ding | Multi-objective disassembly line balancing via modified ant colony optimization algorithm[END_REF]; Massoud and Gupta [START_REF] Massoud | Linear physical programming for solving the multi-criteria disassembly-to-order problem under stochastic yields, limited supply, and quantity discount[END_REF][START_REF] Massoud | Preemptive goal programming for solving the multi-criteria disassembly-to-order problem under stochastic yields, limited supply, and quantity discount[END_REF]; Kongar and Gupta [START_REF] Kongar | A multi-criteria decision making approach for disassembly-to-order systems[END_REF]; Ondemir and Gupta [START_REF] Ondemir | Order-driven component and product recovery for Sensor-embedded Products (SEPS) using linear physical programming[END_REF]; Guo et al. [START_REF] Guo | An improved multi-objective scatter search approach for solving selective disassembly optimization problem[END_REF]; Wang et al. [START_REF] Wang | A hybrid genetic algorithm for multi-objective product plan selection problem with ASP and ALB[END_REF]; Avikal et al. [START_REF] Avikal | An AHP and PROMETHEE methods-based environment friendly heuristic for disassembly line balancing problems[END_REF][START_REF] Avikal | A PROMETHEE method based heuristic for disassembly line balancing problem[END_REF]; Rickli and Camelio [START_REF] Rickli | Multi-objective partial disassembly optimization based on sequence feasibility[END_REF]; Aydemir-Karadag and Turkbey [START_REF] Aydemir-Karadag | Multi-objective optimization of stochastic disassembly line balancing with station paralleling[END_REF]; Avikal et al. [START_REF] Avikal | A fuzzy AHP and PROMETHEE methodbased heuristic for disassembly line balancing problems[END_REF]; Ghazilla et al. [START_REF] Ghazilla | Development of decision support system for fastener selection in product recovery oriented design[END_REF]; Kalayci and Gupta [START_REF] Kalayci | A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem[END_REF][START_REF] Kalayci | Ant colony optimization for sequence-dependent disassembly line balancing problem[END_REF][START_REF] Kalayci | Artificial bee colony algorithm for solving sequence-dependent disassembly line balancing problem[END_REF][START_REF] Kalayci | Balancing a sequence-dependent disassembly line using simulated annealing algorithm[END_REF][START_REF] Kalayci | River formation dynamics approach for sequencedependent disassembly line balancing problem[END_REF][START_REF] Kalayci | A tabu search algorithm for balancing a sequencedependent disassembly line[END_REF]; Ondemir and Gupta [START_REF] Ondemir | A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system[END_REF][START_REF] Ondemir | Quality management in product recovery using the Internet of Things: an optimization approach[END_REF]. Reverse logistics and CLSC network design Pochampally et al. [START_REF] Pochampally | Identification of potential recovery facilities for designing a reverse supply chain network using physical programming[END_REF]; Pochampally and Gupta [START_REF] Pochampally | A linear physical programming approach for designing a reverse supply chain[END_REF]; Gupta and Nukala [START_REF] Gupta | A fuzzy AHP-based approach for selecting potential recovery facilities in a closed loop supply chain[END_REF]; Nukala and Gupta [START_REF] Nukala | Strategic and tactical planning of a closed-loop supply chain network: a linear physical programming approach[END_REF][START_REF] Nukala | A fuzzy mathematical programming approach for supplier selection in a closed-loop supply chain network[END_REF]; Pochampally and Gupta [START_REF] Pochampally | A multiphase fuzzy logic approach to strategic planning of a reverse supply chain network[END_REF]; Pochampally et al. [START_REF] Pochampally | Quantitative decision-making techniques for reverse/closed-loop supply chain design[END_REF]; Tuzkaya and Gulsun [START_REF] Tuzkaya | Evaluating centralized return centers in a reverse logistics network: an integrated fuzzy multi-criteria decision approach[END_REF]; Dehghanian and Mansour [START_REF] Dehghanian | Designing sustainable recovery network of end-of-life products using genetic algorithm[END_REF]; Pochampally et al. [START_REF] Pochampally | Metrics for performance measurement of a reverse/closed-loop supply chain[END_REF][START_REF] Pochampally | Strategic planning models for reverse and closed-loop supply chains[END_REF]; Barker and Zabinsky [START_REF] Barker | A multicriteria decision making model for reverse logistics using analytical hierarchy process[END_REF]; Buyukozkan and Berkol [START_REF] Buyukozkan | Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment[END_REF]; Harraz and Galal [START_REF] Harraz | Design of sustainable end-of-life vehicle recovery network in Egypt[END_REF]; Chaabane et al. [START_REF] Chaabane | Designing supply chains with sustainability considerations[END_REF]; Sasikumar and Haq [START_REF] Sasikumar | Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling[END_REF]; Wang et al. [START_REF] Wang | A multi-objective optimization for green supply chain network design[END_REF]; Paksoy et al. [START_REF] Paksoy | Fuzzy multi-objective optimization of a green supply chain network with risk management that includes environmental hazards[END_REF]; Jamshidi et al. [START_REF] Jamshidi | Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method[END_REF]; Ilgin and Gupta [START_REF] Ilgin | Remanufacturing modeling and analysis[END_REF]; Pochampally and Gupta [START_REF] Pochampally | Use of linear physical programming and Bayesian updating for design issues in reverse logistics[END_REF]; Mehrbod et al. [START_REF] Mehrbod | Interactive fuzzy goal programming for a multi-objective closed-loop logistics network[END_REF]; Pishvaee and Razmi [START_REF] Pishvaee | Environmental supply chain network design using multi-objective fuzzy mathematical programming[END_REF]; Samanlioglu [START_REF] Samanlioglu | A multi-objective mathematical model for the industrial hazardous waste location-routing problem[END_REF]; Ramezani et al. [START_REF] Ramezani | A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level[END_REF]; Özkır and Bas ¸lıgil [START_REF] Özkır | Multi-objective optimization of closed-loop supply chains in uncertain environment[END_REF]; Ozceylan and Paksoy [START_REF] Ozceylan | Fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network[END_REF][START_REF] Ozceylan | A mixed integer programming model for a closed-loop supply-chain network[END_REF]; Shokohyar and Mansour [START_REF] Shokohyar | Simulation-based optimisation of a sustainable recovery network for Waste from Electrical and Electronic Equipment (WEEE)[END_REF]; Ghorbani et al. [START_REF] Ghorbani | A multi-objective fuzzy goal programming model for reverse supply chain design[END_REF]; Mirakhorli [START_REF] Mirakhorli | Fuzzy multi-objective optimization for closed loop logistics network design in bread-producing industries[END_REF]; Nurjanni et al. [START_REF] Nurjanni | Green supply chain design with multi-objective optimization[END_REF]; Wang et al. [START_REF] Wang | Genetic algorithm approach for multi-objective green supply chain design[END_REF]. Third party reverse logistic provider selection Meade and Sarkis [START_REF] Meade | A conceptual model for selecting and evaluating third-party reverse logistics providers[END_REF]; Efendigil et al. [START_REF] Efendigil | A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness[END_REF]; Kannan et al. [START_REF] Kannan | A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider[END_REF]; Saen [START_REF] Saen | A mathematical model for selecting third-party reverse logistics providers[END_REF]; Cheng and Lee [START_REF] Cheng | Outsourcing reverse logistics of high-tech manufacturing firms by using a systematic decision-making approach: TFT-LCD sector in Taiwan[END_REF]; Saen [START_REF] Saen | A new model for selecting third-party reverse logistics providers in the presence of multiple dual-role factors[END_REF][START_REF] Saen | A decision model for selecting third-party reverse logistics providers in the presence of both dual-role factors and imprecise data[END_REF]; Azadi and Saen [START_REF] Azadi | A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors[END_REF]; Zhou et al. [START_REF] Zhou | Selection of optimal third-party logistics recycler based on fuzzy DEA[END_REF]; Ravi [START_REF] Ravi | Selection of third-party reverse logistics providers for end-of-life computers using TOPSIS-AHP based approach[END_REF]; Govindan et al. [START_REF] Govindan | An analytic network process-based multicriteria decision making model for a reverse supply chain[END_REF]; Zareinejad and Javanmard [START_REF] Zareinejad | Evaluation and selection of a third-party reverse logistics provider using ANP and IFG-MCDM methodology[END_REF]; Senthil et al. [START_REF] Senthil | A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics[END_REF]. Evaluation of reverse logistics and green initiatives Ravi et al. [START_REF] Ravi | Selection of a reverse logistics project for end-of-life computers: ANP and goal programing approach[END_REF]; Chiou et al. [START_REF] Chiou | Comparative investigation on green supplier selection of the American, Japanese and Taiwanese electronics industry in China[END_REF]; Sarmiento and Thomas [START_REF] Sarmiento | Identifying improvement areas when implementing green initiatives using a multitier AHP approach[END_REF]; Büyüközkan and C ¸iftc ¸i [START_REF] Büyüközkan | Evaluation of the green supply chain management practices: a fuzzy ANP approach[END_REF]; Chiou et al. [START_REF] Chiou | Consideration factors of reverse logistics implementation -a case study of Taiwan's electronics industry[END_REF]; Senthil et al. [START_REF] Senthil | A decision making methodology for the selection of reverse logistics operating channels[END_REF]; Shaverdi et al. [START_REF] Shaverdi | Developing sustainable SCM evaluation model using fuzzy AHP in publishing industry[END_REF]; Lin [START_REF] Lin | Using fuzzy DEMATEL to evaluate the green supply chain management practices[END_REF]; Wang and Chan [START_REF] Wang | A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives[END_REF]; Mangla et al. [START_REF] Mangla | Multi-objective decision modelling using interpretive structural modelling for green supply chains[END_REF]. Green supplier selection and evaluation Noci [START_REF] Noci | Designing a green vendor rating systems for the assessment of a supplier's environmental performance[END_REF]; Handfield et al. [START_REF] Handfield | Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process[END_REF]; Humphreys et al. [START_REF] Humphreys | Using case-based reasoning to evaluate supplier environmental management performance[END_REF]; Zhang et al. [START_REF] Zhang | Using fuzzy multi-agent decision-making in environmentally conscious supplier management[END_REF]; Humphreys et al. [START_REF] Humphreys | Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process[END_REF]; Nukala and Gupta [START_REF] Nukala | Supplier selection in a closed-loop supply chain network: an ANP-goal programming based methodology[END_REF]; Hsu and Hu [START_REF] Hsu | Application of analytic network process on supplier selection to hazardous substance management in green supply chain management[END_REF]; Lu et al. [START_REF] Lu | Environmental principles applicable to green supplier evaluation by using multi-objective decision analysis[END_REF]; Yang and Wu [START_REF] Yang | Grey entropy method for green supplier selection[END_REF]; Yu-zhong and Li-yun [START_REF]Extension method for green supplier selection[END_REF]; Ge [START_REF] Ge | Research on green suppliers' evaluation based on AHP & genetic algorithm[END_REF]; Hsu and Hu [START_REF] Hsu | Applying hazardous substance management to supplier selection using analytic network process[END_REF]; Lee et al. [START_REF] Lee | A green supplier selection model for high-tech industry[END_REF]; Li and Zhao [START_REF] Li | Selection of suppliers of vehicle components based on green supply chain[END_REF]; Tuzkaya et al. [START_REF] Tuzkaya | Environmental performance evaluation of suppliers: a hybrid fuzzy multi criteria decision approach[END_REF]; Chen et al. [START_REF] Chen | Implementation of green supply chain management in uncertainty[END_REF]; Awasthi et al. [START_REF] Awasthi | A fuzzy multicriteria approach for evaluating environmental performance of suppliers[END_REF]; Grisi et al. [START_REF] Grisi | Supplier performance evaluation for green supply chain management[END_REF]; Kumar and Jain [START_REF] Kumar | Supplier selection: a green approach with carbon footprint monitoring[END_REF]; Feyzioglu and Büyüközkan [START_REF] Feyzioglu | Evaluation of green suppliers considering decision criteria dependencies[END_REF]; Thongchattu and Siripokapirom [START_REF] Thongchattu | Green supplier selection consensus by neural network[END_REF]; Wen and Chi [START_REF] Wen | Developing green supplier selection procedure: a DEA approach[END_REF]; Büyüközkan and C ¸iftc ¸i [START_REF] Büyüközkan | A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information[END_REF]; Ciftci and Buyukozkan [START_REF] Ciftci | A fuzzy MCDM approach to evaluate green suppliers[END_REF]; Sarkis [START_REF] Sarkis | Evaluating environmentally conscious business practices[END_REF][START_REF] Sarkis | A methodological framework for evaluating environmentally conscious manufacturing programs[END_REF]; Rao [START_REF] Rao | An improved compromise ranking method for evaluation of environmentally conscious manufacturing programs[END_REF]; Vinodh et al. [START_REF] Vinodh | Application of analytical network process for the evaluation of sustainable business practices in an Indian relays manufacturing organization[END_REF]; Diabat et al. [START_REF] Diabat | An exploration of green supply chain practices and performances in an automotive industry[END_REF]; Ziout et al. [START_REF] Ziout | Multi-criteria decision support for sustainability assessment of manufacturing system reuse[END_REF]. Evaluation of EOL strategies (EOL option selection) Lee et al. [START_REF] Lee | A multi-objective methodology for evaluating product end-of-life options and disassembly[END_REF]; Kongar et al. [START_REF] Kongar | A fuzzy goal programming approach to disassembly planning[END_REF]; Hula et al. [START_REF] Hula | Multi-criteria decision-making for optimization of product disassembly under multiple situations[END_REF]; Bufardi et al. [START_REF] Bufardi | Multicriteria decisionaid approach for product end-of-life alternative selection[END_REF]; Ravi et al. [START_REF] Ravi | Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach[END_REF]; Kongar and Gupta [START_REF] Kongar | Disassembly to order system under uncertainty[END_REF]; Jun et al. [START_REF] Jun | A multi-objective evolutionary algorithm for EOL product recovery optimization: turbocharger case study[END_REF]; Chan [START_REF] Chan | Product end-of-life options selection: grey relational analysis approach[END_REF]; Chen et al. [START_REF] Chen | Using ANP for the selection of green supply chain management strategies[END_REF]; Wadhwa et al. [START_REF] Wadhwa | Flexible decision modeling of reverse logistics system: a value adding MCDM approach for alternative selection[END_REF]; Iakovou et al. [START_REF] Iakovou | A methodological framework for end-of-life management of electronic products[END_REF]; Rao and Padmanabhan [START_REF] Rao | Selection of best product end-of-life scenario using digraph and matrix methods[END_REF]; Ghazalli and Murata [START_REF] Ghazalli | Development of an AHP-CBR evaluation system for remanufacturing: end-of-life selection strategy[END_REF]; Chen et al. [START_REF] Chen | A business strategy selection of green supply chain management via an analytic network process[END_REF]; Remery et al. [START_REF] Remery | A new method for evaluating the best product end-of-life strategy during the early design phase[END_REF]; Mahapatara et al. [START_REF] Mahapatara | A novel multi-criteria decision making approach for selection of reverse manufacturing alternative[END_REF]; Samantra et al. [START_REF] Samantra | Decision-making in selecting reverse logistics alternative using interval-valued fuzzy sets combined with VIKOR approach[END_REF]; Dhouib [START_REF] Dhouib | An extension of MACBETH method for a fuzzy environment to analyze alternatives in reverse logistics for automobile tire wastes[END_REF]. Evaluation of recycling alternatives and programs Gupta and Isaacs [START_REF] Gupta | Value analysis of disposal strategies for automobiles[END_REF]; Isaacs and Gupta [START_REF] Isaacs | Economic consequences of increasing polymer content for the U.S. automobile recycling infrastructure[END_REF]; Boon et al. [START_REF] Boon | Economic impact of aluminum-intensive vehicles on the U.S. automotive recycling infrastructure[END_REF]; Yu et al. [START_REF] Yu | A decision-making model for materials management of end-of-life electronic products[END_REF]; Boon et al. [START_REF] Boon | End-of-life infrastructure economics for clean vehicles in the United States[END_REF]; Gupta and Pochampally [START_REF] Gupta | Evaluation of recycling programs with respect to drivers of public participation: a fuzzy TOPSIS approach[END_REF]; Yeh and Xu [START_REF] Yeh | Sustainable planning of e-waste recycling activities using fuzzy multicriteria decision making[END_REF]. Operational issues in CLSC Gupta and Evans [START_REF] Gupta | A goal programming model for the operation of closedloop supply chains[END_REF]. Green design Azzone and Noci [START_REF] Azzone | Measuring the environmental performance of new products: an integrated approach[END_REF]; Gungor [START_REF] Gungor | Evaluation of connection types in design for disassembly (DFD) using analytic network process[END_REF]; Kuo et al. [START_REF] Kuo | Environmentally conscious design by using fuzzy multi-attribute decision-making[END_REF]; Choi et al. [START_REF] Choi | A framework for the integration of environmental and business aspects toward sustainable product development[END_REF]; Li et al. [START_REF] Li | A multi-objective fuzzy graph approach for modular formulation considering end-of-life issues[END_REF]; Gao et al. [START_REF] Gao | Selection of green product design scheme based on multi-attribute decision-making method[END_REF]; Kuo [START_REF] Kuo | Combination of case-based reasoning and analytical hierarchy process for providing intelligent decision support for product recycling strategies[END_REF]; Wang et al. [START_REF] Wang | A case study of AHP based model for green product design selection[END_REF]; Vinodh et al. [START_REF] Vinodh | Sustainable concept selection using modified fuzzy TOPSIS: a case study[END_REF]. Performance measurement of GSCs Erol et al. [START_REF] Erol | A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain[END_REF]; Hsu et al. [START_REF] Hsu | Using the FDM and ANP to construct a sustainability balanced scorecard for the semiconductor industry[END_REF]; De Felice and Petrillo [START_REF] De Felice | Hierarchical model to optimize performance in logistics policies: multi attribute analysis[END_REF]; Shaik and Abdul-Kader [START_REF] Shaik | Performance measurement of reverse logistics enterprise: a comprehensive and integrated approach[END_REF]; Bhattacharya et al. [START_REF] Bhattacharya | Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach[END_REF]; Sangwan [START_REF] Sangwan | Evaluation of manufacturing systems based on environmental aspects using a multi-criteria decision model[END_REF]; Mirhedayatian et al. [START_REF] Mirhedayatian | A novel network data envelopment analysis model for evaluating green supply chain management[END_REF]. Inventory problems Bouchery et al. [START_REF] Bouchery | Including sustainability criteria into inventory models[END_REF]. Evaluation of waste treatment strategies Bereketli et al. [START_REF] Bereketli | WEEE treatment strategies' evaluation using fuzzy LINMAP method[END_REF]. Other Walther et al. [START_REF] Walther | Planning and evaluation of sustainable reverse logistics systems[END_REF]; Vadde et al. [START_REF] Vadde | Pricing decisions in a multi-criteria setting for product recovery facilities[END_REF]; Wittstruck and Teuteberg [START_REF] Wittstruck | Integrating the concept of sustainability into the partner selection process: a fuzzy-AHP-TOPSIS approach[END_REF]; Chern et al. [START_REF] Chern | Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multicommodity supply chain network[END_REF]; Liu and Huang [START_REF] Liu | Reduction of power consumption and carbon footprints by applying multi-objective optimisation via genetic algorithms[END_REF]. Green supplier development Dou et al. [START_REF] Dou | Evaluating green supplier development programs with a grey-analytical network process-based methodology[END_REF]. Partner selection Yeh and Chuang [START_REF] Yeh | Using multi-objective genetic algorithm for partner selection in green supply chain problems[END_REF].

customers and maximizing total closed-loop supply chain profit.

The mixed integer programming model proposed by Ozceylan and Paksoy [START_REF] Ozceylan | A mixed integer programming model for a closed-loop supply-chain network[END_REF] determines the optimum transportation amounts together with the location of plants and retailers by considering multiple periods and multiple parts. The proposed model is based on the minimization of transportation, purchasing, refurbishing and fixed costs and scenario analysis is used to investigate the effect of various parameters (demand, capacity etc.). Ozceylan and Paksoy [START_REF] Ozceylan | Fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network[END_REF] develop a fuzzy multi-objective linear programming model for the design of a closed-loop supply chain by considering the uncertainty associated with capacity, demand and reverse rates.

There are two objectives of the model: minimization of total manufacturing and distribution costs and minimization of total fixed costs of plants and retailers. Mirakhorli [START_REF] Mirakhorli | Fuzzy multi-objective optimization for closed loop logistics network design in bread-producing industries[END_REF] proposes an interactive fuzzy multi-objective linear programming model to solve a fuzzy bi-objective (viz., minimization of total cost and minimization of total delivery time) reverse logistics network design problem. Pareto optimal solutions are obtained using weighted sum approach. Nurjanni et al. [START_REF] Nurjanni | Green supply chain design with multi-objective optimization[END_REF] integrate three scalarization approaches, namely weighted sum method, weighted Tchebycheff and augmented weighted Tchebycheff to solve the mathematical model associated with a closed-loop supply chain network.

The model minimizes overall costs and carbon dioxide emissions. Samanlioglu [START_REF] Samanlioglu | A multi-objective mathematical model for the industrial hazardous waste location-routing problem[END_REF] proposes a multi-objective mixed integer model for the location-routing decisions of industrial hazardous material management. Minimization of the total cost, minimization of the total transportation risk and minimization of the total risk for the population around treatment and disposal centers are the objectives of the model and the multi-objective programming model is solved by using lexicographic weighted Tchebycheff method. Bouchery et al. [START_REF] Bouchery | Including sustainability criteria into inventory models[END_REF] reformulate the classical economic order quantity model as a multiobjective problem and call it as sustainable order quantity model. They also considered a multi-echelon extension of this model. The set of efficient solutions (Pareto optimal solutions) is analytically characterized for both models. In addition, an interactive procedure helping decision makers in the quick identification of the best option among these solutions is proposed.

Crisp and fuzzy goal programming

Goal programming is an extension of linear programming due to its ability of handling multiple and often conflicting objectives [START_REF] Ignizio | Goal programming and extensions[END_REF]. Two variants of goal programming are prevalent in the literature. The first one is known as lexicographic or preemptive goal programming while the second one is termed weighted or non-preemptive goal programming. Preemptive goal programming assumes that all goals can be clearly prioritized and that satisfying a higher priority goal should carry more importance than a lower priority goal. Non-preemptive goal programming assumes that all goals should be pursued. However, in this case, all deviations from the goals are multiplied by some weights (based on their relative importance) and summed up to form a single utility function that is optimized.

Kongar and Gupta [START_REF] Kongar | A goal programming approach to the remanufacturing supply chain model[END_REF] present a preemptive integer goal programming model for the disassembly-to-order process so as to satisfy various economical, physical and environmental goals simultaneously. Imtanavanich and Gupta [START_REF] Imtanavanich | Calculating disassembly yields in a multicriteria decision-making environment for a disassembly-to-order system[END_REF] use preemptive goal programming for solving the multi-criteria disassembly-to-order problem under stochastic yields. Massoud and Gupta [START_REF] Massoud | Preemptive goal programming for solving the multi-criteria disassembly-to-order problem under stochastic yields, limited supply, and quantity discount[END_REF] extend Imtanavanich and Gupta [START_REF] Imtanavanich | Calculating disassembly yields in a multicriteria decision-making environment for a disassembly-to-order system[END_REF] by using preemptive goal programming to solve a similar problem under stochastic yields, limited supply, and quantity discount.

McGovern and Gupta [START_REF] Mcgovern | Lexicographic goal programming and assessment tools for a combinatorial production problem[END_REF] use lexicographic goal programming to solve disassembly line balancing problem which involves the determination of a sequence of parts for removal from an end of life product that minimizes the resources for disassembly and maximizes the automation of the process and the quality of the parts or materials recovered. In Xanthopoulos and Iakovou [START_REF] Xanthopoulos | On the optimal design of the disassembly and recovery processes[END_REF], lexicographic goal programming is employed to determine the most desirable components of an EOL product to be non-destructively disassembled. Ondemir and Gupta [START_REF] Ondemir | Quality management in product recovery using the Internet of Things: an optimization approach[END_REF] develop a lexicographic mixed-integer goal programming model for an advanced remanufacturing-to-order and disassembly-toorder system utilizing the life-cycle data collected, stored and delivered by the Internet of Things.

Goal programming is employed in Gupta and Isaacs [START_REF] Gupta | Value analysis of disposal strategies for automobiles[END_REF] to investigate the effect of lightweighting on the dismantler and shredder profitabilities associated with EOL vehicle recycling industry of USA. Isaacs and Gupta [START_REF] Isaacs | Economic consequences of increasing polymer content for the U.S. automobile recycling infrastructure[END_REF] propose a goal programming based methodology to explore changes to the current U.S. vehicle recycling infrastructure considering their effects on dismantler and shredder profitabilities. Boon et al. [START_REF] Boon | Economic impact of aluminum-intensive vehicles on the U.S. automotive recycling infrastructure[END_REF] and Boon et al. [START_REF] Boon | End-of-life infrastructure economics for clean vehicles in the United States[END_REF] use goal programming to evaluate the materials streams and process profitabilities for several different aluminum-intensive vehicle (AIV) processing scenarios Gupta and Evans [START_REF] Gupta | A goal programming model for the operation of closedloop supply chains[END_REF] develop a non-preemptive goal programming model for operational planning of closed-loop supply chains considering multiple products and operations associated with the product, subassembly, part and material levels.

Kongar and Gupta [START_REF] Kongar | A multi-criteria decision making approach for disassembly-to-order systems[END_REF] develop a goal programming model of a disassembly-to-order system to determine the best combination of the number of each product type to be taken back at the end-of-life and disassembled to meet the demand for items and materials retrieved from them under a variety of physical, financial and environmental constrains so as to achieve the preemptive goals of maximum total profit, maximum sales from materials, minimum number of disposed items, minimum number of stored items, minimum cost of disposal and minimum cost of preparation, in that order.

Harraz and Galal [START_REF] Harraz | Design of sustainable end-of-life vehicle recovery network in Egypt[END_REF] propose a goal programming based methodology to solve a product recovery network design problem involving the determination of the locations for the different facilities and the amount to be allocated to the different end of life (EOL) options. Chaabane et al. [START_REF] Chaabane | Designing supply chains with sustainability considerations[END_REF] develop a goal programming based sustainable supply chain design methodology by considering carbon emissions, suppliers and sub-contractors selection, total logistics costs, technology acquisition and the choice of transportation modes.

Aspiration levels (goals) are considered concise and precise in goal programming. However, there are many occasions that a decision maker cannot specify the goal values precisely. Fuzzy goal programming takes this uncertainty into consideration by employing the concept of membership functions based on fuzzy set theory [START_REF] Aouni | Fuzzy goal programming model: an overview of the current state-of-the art[END_REF].

Kongar et al. [START_REF] Kongar | A fuzzy goal programming approach to disassembly planning[END_REF] and Kongar and Gupta [START_REF] Kongar | Disassembly to order system under uncertainty[END_REF] use fuzzy goal programming to solve the disassembly-to-order problem defined in Section 1. Mehrbod et al. [START_REF] Mehrbod | Interactive fuzzy goal programming for a multi-objective closed-loop logistics network[END_REF] first develop a multi-objective mixed-integer nonlinear programming formulation for a closedloop supply chain. Then, this model is solved using interactive fuzzy goal programming (IFGP) which has the ability of addressing the imprecise nature of decision-makers' aspiration levels for goals. Ghorbani et al. [START_REF] Ghorbani | A multi-objective fuzzy goal programming model for reverse supply chain design[END_REF] develop a fuzzy goal programming model for the design of a reverse logistics network. Imtanavanich and Gupta [START_REF] Imtanavanich | Weighted fuzzy goal programming approach for a disassembly-to-order system[END_REF] employ weighted fuzzy goal programming to solve the multi-period DTO problem. Imtanavanich and Gupta [START_REF] Imtanavanich | Solving a disassembly-to-order system by using genetic algorithm and weighted fuzzy goal programming[END_REF] integrate genetic algorithms with weighted fuzzy goal programming to solve a similar DTO problem.

Physical programming

Physical programming uses a preference function to represent the decision maker's preference. In physical programming, DM determines a suitable preference function and specifies ranges of different degrees of desirability (desirable, tolerable, undesirable, etc.) for each criterion. There are eight preference functions classified into 8 classes, 4 soft and 4 hard [START_REF] Lambert | Disassembly modeling for assembly, maintenance, reuse, and recycling[END_REF][START_REF] Ilgin | Physical programming: a review of the state of the art[END_REF].

The analysis of the literature showed that the physical programming approach has been mostly used for the network design of reverse and closed-loop supply chains and for planning problems in disassembly-to-order (DTO) systems.

In Pochampally et al. [START_REF] Pochampally | Identification of potential recovery facilities for designing a reverse supply chain network using physical programming[END_REF], linear physical programming (LPP) is employed to identify potential facilities from a set of candidate recovery facilities operating in a region by considering several criteria (viz., quality of products at recovery facility, ratio of throughput to supply of used products, multiplication of throughput by disassembly time, and customer service rating of the recovery facility). Pochampally and Gupta [START_REF] Pochampally | A linear physical programming approach for designing a reverse supply chain[END_REF] develop an LPP-based reverse supply chain design methodology involving three phases. Economical products to be re-processes are selected from a set of candidate cores in phase I. Phase 2 involves the determination of potential recovery facilities using the criteria and classes defined in Pochampally et al. [START_REF] Pochampally | Identification of potential recovery facilities for designing a reverse supply chain network using physical programming[END_REF]. Phase 3 determines the right mix and quantities of products to be transported in the reverse supply chain. The strategic and tactical planning model developed by Nukala and Gupta [START_REF] Nukala | Strategic and tactical planning of a closed-loop supply chain network: a linear physical programming approach[END_REF] determines the following variables simultaneously: the most economical used-product to re-process, efficient production facilities and the right mix and quantity of goods to be transported across the supply chain. Similar models are presented in Pochampally et al. [START_REF] Pochampally | Quantitative decision-making techniques for reverse/closed-loop supply chain design[END_REF][START_REF] Saen | A mathematical model for selecting third-party reverse logistics providers[END_REF] and Ilgin and Gupta [START_REF] Ilgin | Remanufacturing modeling and analysis[END_REF].

Quality function deployment (QFD) and LPP are integrated in Pochampally et al. [START_REF] Pochampally | Metrics for performance measurement of a reverse/closed-loop supply chain[END_REF] to measure the "satisfaction level" of a reverse/closed-loop supply chain with respect to various performance measures such as reputation and innovation. Pochampally et al. [START_REF] Pochampally | Strategic planning models for reverse and closed-loop supply chains[END_REF] present a similar model.

An LPP-based methodology for collection center selection problem is presented in Pochampally and Gupta [START_REF] Pochampally | Use of linear physical programming and Bayesian updating for design issues in reverse logistics[END_REF] considering eight criteria (viz., sigma level (SL), per capital income of people in residential area (PR), utilization of incentives from local government (UG), distance from residential area (DR), distance from highways (DH), incentives from local government (IG), space cost (SC), labor cost (LC)).

An LPP model is developed in Kongar and Gupta [START_REF] Kongar | Disassembly-to-order system using Linear Physical Programming[END_REF] to solve a disassembly to order problem which involves the determination of the number of items to be disassembled for remanufacturing, recycling, storage and disposal. The criteria considered include average customer satisfaction, average quality achievement, resale revenue, recycling revenue, total profit, number of recycled items, average environmental damage, average environmental benefit and number of disposed items. Lambert and Gupta [START_REF] Lambert | Disassembly modeling for assembly, maintenance, reuse, and recycling[END_REF] present a similar model. A DTO problem is modeled by Kongar and Gupta [START_REF] Kongar | Solving the disassembly-to-order problem using linear physical programming[END_REF] considering five goals (number of disposed items, total profit, number of recycled items, environmental damage and customer satisfaction). In Imtanavanich and Gupta [START_REF] Imtanavanich | Linear physical programming approach for a disassembly-to-order system under stochastic yields and product's deterioration[END_REF], LPP is used to solve a multi-period DTO problem. Genetic algorithms and LPP are integrated in Imtanavanich and Gupta [START_REF] Imtanavanich | Evolutionary computation with linear physical programming for solving a disassembly-to-order system[END_REF] to solve a DTO problem. The fitness value of GA is calculated using LPP. A multi-period DTO problem with four objectives (viz., maximization of profit, minimization of procurement cost, minimization of purchase cost and minimization of disposal cost) is solved in Massoud and Gupta [START_REF] Massoud | Linear physical programming for solving the multi-criteria disassembly-to-order problem under stochastic yields, limited supply, and quantity discount[END_REF] by developing an LPP-based solution approach. Optimum disassembly, refurbishment, disposal, recycling and storage plans are determined by the LPP model developed by Ondemir and Gupta [START_REF] Ondemir | Order-driven component and product recovery for Sensor-embedded Products (SEPS) using linear physical programming[END_REF] for a demand-driven environment utilizing the life-cycle data collected, stored and delivered by sensors and RFID tags. Ondemir and Gupta [START_REF] Ondemir | A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system[END_REF] develop an LPP model to optimize a multi-criteria advanced repair-to-order and disassembly-to-order system involving sensor embedded products.

Heuristics and metaheuristics

A heuristic can be defined as a technique which seeks or finds good solutions to a difficult model. A meta-heuristic extends the heuristic concept by exploiting ideas and concepts from another discipline to help solve the artificial system being modeled. Genetic algorithms, simulated annealing and tabu search are the most commonly used metaheuristics [START_REF] Jones | Multi-objective meta-heuristics: an overview of the current state-of-the-art[END_REF]. In this section, we provide an overview of multi objective heuristic and metaheuristic approaches developed to solve ECMPRO related problems.

Gupta and Taleb [START_REF] Gupta | An algorithm to disassemble multiple product structures with multiple occurrence of parts[END_REF] and Taleb and Gupta [START_REF] Taleb | Disassembly of multiple product structures[END_REF] presented a heuristic methodology for disassembling multiple product structures with parts/materials commonality. There are two companion algorithms in this methodology: the "Core Algorithm" and the "Allocation Algorithm". The total disassembly requirements of the root items over the planning horizon are determined by the "Core Algorithm" and the schedule for disassembling the roots and the subassemblies are provided by "Allocation Algorithm". Langella [START_REF] Langella | Heuristics for demand-driven disassembly planning[END_REF] extends this methodology by considering holding costs and external procurement of items.

Genetic algorithms (GA) are numerical optimization algorithms inspired by both natural selection and natural genetics. They are generally used to search large, non-linear search spaces where expert knowledge is lacking or difficult to encode and where traditional optimization methods fall short [START_REF] Goldberg | Genetic algorithms in search, optimization, and machine learning[END_REF]. GAs are by far the most frequently used metaheuristic to solve ECMPRO related problems. Jun et al. [START_REF] Jun | A multi-objective evolutionary algorithm for EOL product recovery optimization: turbocharger case study[END_REF] develop a multi-objective evolutionary algorithm to determine the best EOL option. In Hula et al. [START_REF] Hula | Multi-criteria decision-making for optimization of product disassembly under multiple situations[END_REF], multi objective GA is used to determine the most appropriate EOL option. The green supply chain partner selection problem is solved in Yeh and Chuang [START_REF] Yeh | Using multi-objective genetic algorithm for partner selection in green supply chain problems[END_REF] by developing two multi objective genetic algorithms. The multi-objective genetic algorithm developed by Sakundarini et al. [START_REF] Sakundarini | Multi-objective optimization for high recyclability material selection using genetic algorithm[END_REF] considers technical, economic and recyclability requirements for the selection of materials with high recyclability. Rickli and Camelio [START_REF] Rickli | Multi-objective partial disassembly optimization based on sequence feasibility[END_REF] develop a multi-objective genetic algorithm to optimize partial disassembly sequences based on disassembly operation costs, recovery reprocessing costs, revenues and environmental impacts. Chern et al. [START_REF] Chern | Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multicommodity supply chain network[END_REF] develop a heuristic called genetic algorithms based master planning algorithm (GAMPA) which solves the master planning problem of a supply chain network involving multiple final products, substitutions, and a recycling process. Liu and Huang [START_REF] Liu | Reduction of power consumption and carbon footprints by applying multi-objective optimisation via genetic algorithms[END_REF] use multi objective genetic algoritms to solve two scheduling problems involving economic and environment-related criteria. Wang et al. [START_REF] Wang | Genetic algorithm approach for multi-objective green supply chain design[END_REF] present an application of multi-objective genetic algorithms in closed-loop supply chain network design.

Besides GAs, researchers have applied several other metaheuristics to ECMPRO related problems. Guo et al. [START_REF] Guo | An improved multi-objective scatter search approach for solving selective disassembly optimization problem[END_REF] propose a multi-objective scatter search algorithm to solve the selective disassembly problem which involves the determination of optimal disassembly sequences for single or multiple target components. Jamshidi et al. [START_REF] Jamshidi | Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method[END_REF] develop a mathematical model for the design of a supply chain by simultaneously considering cost and anvironmental effect. A memetic algorithm integrated with the Taguchi method is utilized to solve the model.

Disassembly Line Balancing Problem (DLBP) is an important and actively researched problem in ECMPRO (see McGovern and Gupta [START_REF] Mcgovern | The disassembly line: balancing and modeling[END_REF] for more information on DLBP). It is a multi-objective problem as described by Gungor and Gupta [START_REF] Gungor | Disassembly line in product recovery[END_REF] and has been mathematically proven to be NP-complete by McGovern and Gupta [START_REF] Mcgovern | A balancing method and genetic algorithm for disassembly line balancing[END_REF] which makes the desire to achieve the best balance computationally expensive when considering large sized problems. Thus, the need to obtain near optimal solutions efficiently have led various authors to use a variety of heuristic and metaheuristic techniques such as

• genetic algorithms (GA) [START_REF] Mcgovern | A balancing method and genetic algorithm for disassembly line balancing[END_REF][START_REF] Aydemir-Karadag | Multi-objective optimization of stochastic disassembly line balancing with station paralleling[END_REF],

• ant colony optimization (ACO) [START_REF] Agrawal | A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem[END_REF][START_REF] Kalayci | Ant colony optimization for sequence-dependent disassembly line balancing problem[END_REF],

• simulated annealing (SA) [START_REF] Kalayci | Balancing a sequence-dependent disassembly line using simulated annealing algorithm[END_REF],

• tabu search (TS) [START_REF] Kalayci | A tabu search algorithm for balancing a sequencedependent disassembly line[END_REF],

• artificial bee colony (ABC) [START_REF] Kalayci | Artificial bee colony algorithm for solving sequence-dependent disassembly line balancing problem[END_REF],

• particle swarm optimization (PSO) [START_REF] Kalayci | A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem[END_REF],

• river formation dynamics (RFD) [START_REF] Kalayci | River formation dynamics approach for sequencedependent disassembly line balancing problem[END_REF].

Battaia and Dolgui [START_REF] Battaia | A taxonomy of line balancing problems and their solution approaches[END_REF] and Delorme et al. [START_REF] Delorme | Multi-objective approaches for design of assembly lines[END_REF] present an overview of multi-objective approaches developed for the design of assembly and disassembly lines.

Integration of simulation and optimization techniques

Simulation is generally employed to analyze complex processes or systems. It involves the development and analysis of models that have the ability of imitating the behavior of the system being analyzed [START_REF] Pegden | Introduction to simulation using SIMAN[END_REF].

Shokohyar and Mansour [START_REF] Shokohyar | Simulation-based optimisation of a sustainable recovery network for Waste from Electrical and Electronic Equipment (WEEE)[END_REF] deal with the electronic waste management problem of Iran by developing a simulationoptimization model which determines the locations for collection centers and recycling plants. Fuzzy controlled agent based simulation framework proposed by Zhang et al. [START_REF] Zhang | Using fuzzy multi-agent decision-making in environmentally conscious supplier management[END_REF] evaluates the environmental performance of the suppliers.

Multi-criteria analysis techniques

While the multi-objective optimization techniques search for new solutions in solution space, multi-criteria analysis techniques consider limited number of predetermined alternatives and discrete preference ratings [START_REF] Tzeng | Multiple attribute decision making: methods and applications[END_REF]. In this section, we present such techniques as analytical hierarchy process, fuzzy analytical hierarchy process, analytical network process, data envelopment analysis, DEMATEL, TOPSIS, ELECTRE, PROMETHEE, multi attribute utility theory, VIKOR, MACBETH, case based reasoning, gray relational analysis, and others.

Analytical hierarchy process

The analytical hierarchy process (AHP) is a multi-criteria decision making tool formalized by Saaty [START_REF] Saaty | The analytic hierarchy process[END_REF]. It uses simple mathematics to support decision makers in explicitly weighing tangible and intangible criteria against each other for the purpose of resolving conflict or setting priorities.

Azzone and Noci [START_REF] Azzone | Measuring the environmental performance of new products: an integrated approach[END_REF] use AHP to evaluate the environmental performance of alternative product designs. In Choi et al. [START_REF] Choi | A framework for the integration of environmental and business aspects toward sustainable product development[END_REF], the relative importance of five design for environment strategies are compared using AHP. Wang et al. [START_REF] Wang | A case study of AHP based model for green product design selection[END_REF] develop an AHP-based green product design selection methodology which does not require the designers to conduct detailed analysis (e.g., life-cycle assessment) for every new product option. Kim et al. [START_REF] Kim | An assessment of the recycling potential of materials basedon environmental and economic factors; case study in South Korea[END_REF] employ AHP to evaluate the recycling potential of materials based on environmental and economic factors.

Noci [START_REF] Noci | Designing a green vendor rating systems for the assessment of a supplier's environmental performance[END_REF] proposes a green vendor rating system using AHP. Handfield et al. [START_REF] Handfield | Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process[END_REF] develop an AHP-based methodology to assess the relative performance of several suppliers considering environmental issues. Dai and Blackhurst [START_REF] Dai | A four-phase AHP-QFD approach for supplier assessment: a sustainability perspective[END_REF] develop a four-phase methodology for sustainable supplier assessment by integrating quality function deployment (QFD) and AHP. First, customer requirements are linked with the company's sustainability strategy. Then the sustainable purchasing competitive priority is determined. Next, sustainable supplier assessment criteria are developed. Finally, AHP is employed to assess the suppliers. Shaik and Abdul-Kader [START_REF] Shaik | Performance measurement of reverse logistics enterprise: a comprehensive and integrated approach[END_REF] first develop a reverse logistics performance measurement system which is based on balanced score card and performance prism. Then, AHP is integrated with this system to calculate the overall comprehensive performance index (OCPI).

Barker and Zabinsky [START_REF] Barker | A multicriteria decision making model for reverse logistics using analytical hierarchy process[END_REF] use sensitivity analysis with AHP to provide insights into the preference ordering among eight alternative reverse logistics network configurations. In Jiang et al. [START_REF] Jiang | Development of multi-criteria decision making model for remanufacturing technology portfolio selection[END_REF], AHP is used for remanufacturing portfolio selection. Ziout et al. [START_REF] Ziout | Multi-criteria decision support for sustainability assessment of manufacturing system reuse[END_REF] develop an AHP-based methodology to evaluate the sustainability level of manufacturing systems. The AHP-based methodology proposed by Sarmiento and Thomas [START_REF] Sarmiento | Identifying improvement areas when implementing green initiatives using a multitier AHP approach[END_REF] identifies improvement areas in the implementation of green initiatives. Subramoniam et al. [START_REF] Subramoniam | Remanufacturing Decision-Making Framework (RDMF): research validation using the analytical hierarchical process[END_REF] use AHP to validate the Reman Decision-Making Framework (RDMF) developed in Subramoniam et al. [START_REF] Subramoniam | Aftermarket remanufacturing strategic planning decision-making framework: theory and practice[END_REF].

Fuzzy analytical hierarchy process

There are two characteristics of AHP often criticized in the literature: use of unbalanced scale of judgments and its inability to adequately handle the inherent uncertainty and imprecision in the pair-wise comparison process [START_REF] Ertugrul | Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods[END_REF]. Fuzzy analytical process which integrates AHP with the concepts of fuzzy set theory is often used by reserachers to overcome these limitations of AHP.

AHP and fuzzy multi attribute decison making are integrated in the environmentally conscious design methodology proposed by Kuo et al. [START_REF] Kuo | Environmentally conscious design by using fuzzy multi-attribute decision-making[END_REF]. Li et al. [START_REF] Li | A multi-objective fuzzy graph approach for modular formulation considering end-of-life issues[END_REF] integrate AHP and fuzzy logic to determine an optimal modular formulation in modular product design with environmental considerations.

Yu et al. [START_REF] Yu | A decision-making model for materials management of end-of-life electronic products[END_REF] use fuzzy AHP to determine the most appropriate recycling option for EOL products considering three criteria: environmental impact, recycling associated cost and recoverable material content.

In Lu et al. [START_REF] Lu | Environmental principles applicable to green supplier evaluation by using multi-objective decision analysis[END_REF], Lee et al. [START_REF] Lee | A green supplier selection model for high-tech industry[END_REF], Grisi et al. [START_REF] Grisi | Supplier performance evaluation for green supply chain management[END_REF], Ciftci and Buyukozkan [START_REF] Ciftci | A fuzzy MCDM approach to evaluate green suppliers[END_REF] and Amin and Zhang [START_REF] Amin | An integrated model for closed-loop supply chain configuration and supplier selection: multi-objective approach[END_REF], fuzzy AHP is used to integrate environmental factors into supplier evaluation process. Lee et al. [START_REF] Lee | Using FAHP to determine the criteria for partner's selection within a green supply chain: the case of hand tool industry in Taiwan[END_REF] propose a fuzzy AHP based approach to determine the most important criteria for green supplier selection in the Taiwanese hand tool industry. In Chiou et al. [START_REF] Chiou | Comparative investigation on green supplier selection of the American, Japanese and Taiwanese electronics industry in China[END_REF], fuzzy AHP is employed to compare the green supply chain management (GSCM) practices of American, Japanese and Taiwanese electronics manufacturers operating in China. Chiou et al. [START_REF] Chiou | Consideration factors of reverse logistics implementation -a case study of Taiwan's electronics industry[END_REF] employ fuzzy AHP to select the most important criteria in reverse logistics implementation. Efendigil et al. [START_REF] Efendigil | A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness[END_REF] present an approach integrating fuzzy AHP and artificial neural Networks for the third party reverse logistics provider selection problem.

Gupta and Nukala [START_REF] Gupta | A fuzzy AHP-based approach for selecting potential recovery facilities in a closed loop supply chain[END_REF] use fuzzy AHP to identify potential facilities in a set of candidate recovery facilities operating in a region. Shaverdi et al. [START_REF] Shaverdi | Developing sustainable SCM evaluation model using fuzzy AHP in publishing industry[END_REF] employ fuzzy-AHP to determine the effective factors associated with the sustainable supply chain management in publishing industry.

De Felice and Petrillo [START_REF] De Felice | Hierarchical model to optimize performance in logistics policies: multi attribute analysis[END_REF] integrate AHP and simulation to simultaneously improve the performance of inventory management and reverse logistics management.

The approach proposed by Punniyamoorty et al. [START_REF] Punniyamoorty | A combined application of structural equation modeling (SEM) and analytic hierarchy process (AHP) in supplier selection[END_REF] combines AHP and structural equation modeling (SEM) for the selection of suppliers considering economic as well as environmental factors.

Thongchattu and Siripokapirom [START_REF] Thongchattu | Green supplier selection consensus by neural network[END_REF] model the green supplier selection problem using AHP. Neural Networks are used to determine criteria weights.

Analytical network process

Analytical network process (ANP) was developed by Saaty [START_REF] Saaty | Decision making with dependence and feedback: the analytic network process[END_REF] as a generalization of AHP. It releases the restrictions of hierarchical AHP structure by modeling the decision problem as an influence network of clusters and nodes contained within the clusters.

ANP is used in Cheng and Lee [START_REF] Cheng | Outsourcing reverse logistics of high-tech manufacturing firms by using a systematic decision-making approach: TFT-LCD sector in Taiwan[END_REF] for investigating the relative importance of service requirements as well as selecting an appropriate third party reverse logistics provider. Meade and Sarkis [START_REF] Meade | A conceptual model for selecting and evaluating third-party reverse logistics providers[END_REF] employ ANP for the evaluation and selection of third party reverse logistics providers. Hsu and Hu [START_REF] Hsu | Application of analytic network process on supplier selection to hazardous substance management in green supply chain management[END_REF] and Hsu and Hu [START_REF] Hsu | Applying hazardous substance management to supplier selection using analytic network process[END_REF] integrate hazardous substance management to supplier selection using analytical network process (ANP). Büyüközkan and C ¸iftc ¸i [START_REF] Büyüközkan | Evaluation of the green supply chain management practices: a fuzzy ANP approach[END_REF] use fuzzy ANP to evaluate green supply chain management practices of an automotive company. Büyüközkan and C ¸iftc ¸i [START_REF] Büyüközkan | A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information[END_REF] propose a fuzzy ANP based methodology for sustainable supplier selection.

Ravi et al. [START_REF] Ravi | Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach[END_REF] use ANP together with BSC to determine the most suitable EOL option for EOL computers. Chen et al. [START_REF] Chen | A business strategy selection of green supply chain management via an analytic network process[END_REF] solve green supply chain management strategy selection problem of a Taiwanese electronics company using ANP.

Sarkis [START_REF] Sarkis | Evaluating environmentally conscious business practices[END_REF] employs ANP to evaluate environmentally conscious business practices. In Vinodh et al. [START_REF] Vinodh | Application of analytical network process for the evaluation of sustainable business practices in an Indian relays manufacturing organization[END_REF], environmentally conscious business practice model proposed by Sarkis [START_REF] Sarkis | Evaluating environmentally conscious business practices[END_REF] is adopted for the evaluation of sustainable business practicess in an Indian relays manufacturing organization. Chen et al. [START_REF] Chen | Using ANP for the selection of green supply chain management strategies[END_REF] use ANP to evaluate several green supply chain management strategies (viz., green design, green purchasing, green marketing, green manufacturing). Bhattacharya et al. [START_REF] Bhattacharya | Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach[END_REF] develop an intra-organizational collaborative decision-making (CDM) approach for performance measurement of a green supply chain (GSC) by integrating fuzzy ANP and balanced score card. Tuzkaya and Gulsun [START_REF] Tuzkaya | Evaluating centralized return centers in a reverse logistics network: an integrated fuzzy multi-criteria decision approach[END_REF] integrate ANP with fuzzy TOPSIS to evaluate centralized return centers in a reverse logistics network.

Gungor [START_REF] Gungor | Evaluation of connection types in design for disassembly (DFD) using analytic network process[END_REF] develops an ANP-based methodology to evaluate connection types in design for disassembly.

Govindan et al. [START_REF] Govindan | An analytic network process-based multicriteria decision making model for a reverse supply chain[END_REF] develop a two-phase model for the selection of third party reverse logistics providers. In this model, AHP is employed to identify the most prioritized factors while ANP is used to select the reverse logistic providers.

Data envelopment analysis

Data envelopment analysis (DEA) is used to evaluate the performance of a set of peer entities called Decision Making Units (DMUs) which convert multiple inputs into multiple outputs [START_REF] Cooper | Data envelopment analysis: history, models, and interpretations[END_REF].

Kumar and Jain [START_REF] Kumar | Supplier selection: a green approach with carbon footprint monitoring[END_REF] develop a DEA model of green supplier selection by considering carbon footprints of suppliers as a necessary dual role factor. Mirhedayatian et al. [START_REF] Mirhedayatian | A novel network data envelopment analysis model for evaluating green supply chain management[END_REF] evaluate the performance of green supply chains by developing a network DEA model involving dual-role factors, undesirable outputs and fuzzy data.

The data envelopment analysis based methodology proposed by Saen [START_REF] Saen | A mathematical model for selecting third-party reverse logistics providers[END_REF] determines the most efficient third party reverse logistics (3PL) provider considering quantitative and qualitative data. Saen [START_REF] Saen | A new model for selecting third-party reverse logistics providers in the presence of multiple dual-role factors[END_REF] proposes a DEA based third party reverse logistic provider selection methodology for the case of multiple dual factors while Saen [START_REF] Saen | A decision model for selecting third-party reverse logistics providers in the presence of both dual-role factors and imprecise data[END_REF] and Azadi and Saen [START_REF] Azadi | A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors[END_REF] provide 3PL selection models involving both multiple dual factors and imprecise data. Zhou et al. [START_REF] Zhou | Selection of optimal third-party logistics recycler based on fuzzy DEA[END_REF] develop a fuzzy confidence DEA model to select third-party recyclers.

Wen and Chi [START_REF] Wen | Developing green supplier selection procedure: a DEA approach[END_REF] integrate AHP/ANP with DEA for developing a green supplier selection procedure. First, DEA distinguishes the efficient candidates of suppliers from the entire group. Then, AHP/ANP is used for further analysis without making efforts on unnecessary suppliers.

Sarkis [START_REF] Sarkis | A methodological framework for evaluating environmentally conscious manufacturing programs[END_REF] integrates ANP and data envelopment analysis (DEA) to evaluate environmentally conscious manufacturing programs. Kuo and Lin [START_REF] Kuo | Supplier selection using analytic network process and data envelopment analysis[END_REF] develop a methodology by coupling ANP and DEA for green supplier selection.

DEMATEL

DEMATEL (Decision Making and Evaluation Laboratory

) method is used to identify causal relationships among the elements of a system. The main output of this technique is a causal diagram which uses digraphs instead of directionless graphs to describe the contextual relationships and the strengths of influence among the elements [START_REF] Wu | Choosing knowledge management strategies by using a combined ANP and DEMATEL approach[END_REF].

Lin [START_REF] Lin | Using fuzzy DEMATEL to evaluate the green supply chain management practices[END_REF] uses fuzzy-DEMATEL to analyze the interrelationships among three issues (green supply chain management practices, organizational performance and external driving factors) associated with green supply chain management implementation.

TOPSIS

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) determines the best alternative based on the concept of compromise solution which has the shortest distance from the ideal solution and the greatest distance from the negative ideal solution in an Euclidean sense [START_REF] Tzeng | Multiple attribute decision making: methods and applications[END_REF].

Gupta and Pochampally [START_REF] Gupta | Evaluation of recycling programs with respect to drivers of public participation: a fuzzy TOPSIS approach[END_REF] propose a fuzzy-TOPSIS based approach for the evaluation of recycling programs with respect to drivers of public participation. Remery et al. [START_REF] Remery | A new method for evaluating the best product end-of-life strategy during the early design phase[END_REF] propose a TOPSIS-based end of life option selection methodology called ELSEM while Wadhwa et al. [START_REF] Wadhwa | Flexible decision modeling of reverse logistics system: a value adding MCDM approach for alternative selection[END_REF] use fuzzy TOPSIS for option selection problem in reverse logistics. Gao et al. [START_REF] Gao | Selection of green product design scheme based on multi-attribute decision-making method[END_REF] construct a fuzzy TOPSIS model to evaluate a set of feasible green design alternatives. A fuzzy TOPSIS approach is proposed in Yeh and Xu [START_REF] Yeh | Sustainable planning of e-waste recycling activities using fuzzy multicriteria decision making[END_REF] for the evaluation of alternative recycling activities of a recycling company considering various sustainability criteria with environmental, economic, and social dimensions. Vinodh et al. [START_REF] Vinodh | Sustainable concept selection using modified fuzzy TOPSIS: a case study[END_REF] use fuzzy TOPSIS to determine the best sustainable concept among five sustainable concepts (viz., design for environment, life cycle assessments, environmental conscious quality function deployment, theory of inventive problem solving and life cycle impact assessment). Mahapatara et al. [START_REF] Mahapatara | A novel multi-criteria decision making approach for selection of reverse manufacturing alternative[END_REF] develop a fuzzy TOPSIS methodology to evaluate different reverse manufacturing alternatives (remanufacturing, reselling, repairing, cannibalisation and Refurbishing). Diabat et al. [START_REF] Diabat | An exploration of green supply chain practices and performances in an automotive industry[END_REF] develop a fuzzy-TOPSIS-based methodology to assess the importance of GSCM practices and performances in an automotive company.

Kannan et al. [START_REF] Kannan | A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider[END_REF] integrate interpretive structural modeling and fuzzy TOPSIS in order to select the best third party reverse logistics provider. Awasthi et al. [START_REF] Awasthi | A fuzzy multicriteria approach for evaluating environmental performance of suppliers[END_REF], Govindan et al. [START_REF] Govindan | A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach[END_REF] and Shen et al. [START_REF] Shen | A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences[END_REF] use fuzzy TOPSIS to generate an overall performance score for measuring the environmental performance of suppliers.

Wittstruck and Teuteberg [START_REF] Wittstruck | Integrating the concept of sustainability into the partner selection process: a fuzzy-AHP-TOPSIS approach[END_REF] integrate fuzzy AHP and TOPSIS for recycling partner selection. Senthil et al. [START_REF] Senthil | A decision making methodology for the selection of reverse logistics operating channels[END_REF] determine the best reverse logistics operating channel by combining AHP and fuzzy TOPSIS. Wang and Chan [START_REF] Wang | A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives[END_REF] integrate fuzzy TOPSIS and AHP for the evaluation of new green initiatives. In Ravi [START_REF] Ravi | Selection of third-party reverse logistics providers for end-of-life computers using TOPSIS-AHP based approach[END_REF] and Senthil et al. [START_REF] Senthil | A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics[END_REF], AHP-TOPSIS integration is employed for the selection of third party reverse logistics providers.

ELECTRE

ELECTRE (ELimination Et Choix Traduisant la REalité (in French) which means, elimination and choice expressing reality) performs pair-wise comparisons among alternatives for each one of the attributes separately to establish outranking relationships between the alternatives [START_REF] Bari | Application of ELECTRE to network selection in a hetereogeneous wireless network environment[END_REF]. These outranking relations are built in such a way that it is possible to compare alternatives. The information required by ELECTRE consists of information among the criteria and information within each criterion [START_REF] De Almeida | Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method[END_REF].

Bufardi et al. [START_REF] Bufardi | Multicriteria decisionaid approach for product end-of-life alternative selection[END_REF] employ ELECTRE III for the selection of the best EOL alternative.

PROMETHEE

PROMETHEE (preference ranking organization method for enrichment evaluation) is a prescriptive method that enables a decision maker to rank the alternatives according to the his/her preferences. It requires a preference function associated with each criterion as well as weights indicating their relative importance. While the PROMETHEE I gives partial ranking of alternatives PROMETHEE II gives a complete ranking [START_REF] Brans | Promethee methods. In: Multiple criteria decision analysis: state of the art surveys[END_REF][START_REF] Mareschal | Visual PROMETHEE: developments of the PROMETHEE and GAIA multicriteria decision aid methods[END_REF].

Avikal et al. [START_REF] Avikal | A PROMETHEE method based heuristic for disassembly line balancing problem[END_REF] develop a PROMETHEE based methodology for assigning the disassembly tasks to workstations of a disassembly line. Ghazilla et al. [START_REF] Ghazilla | Development of decision support system for fastener selection in product recovery oriented design[END_REF] use PROMETHEE to evaluate alternative fasteners in design for disassembly.

Avikal et al. [START_REF] Avikal | An AHP and PROMETHEE methods-based environment friendly heuristic for disassembly line balancing problems[END_REF] solve the disassembly line balancing problem by developing an AHP-TOPSIS based methodology. In the proposed heuristic, the important criteria, which play a significant role in the product disassembly process, are selected. Then AHP is applied to calculate the weight of each criterion. Finally, PROMETHEE uses these weights to determine the ranking of the tasks for the assignment to the disassembly stations. Avikal et al. [START_REF] Avikal | A fuzzy AHP and PROMETHEE methodbased heuristic for disassembly line balancing problems[END_REF] modify Avikal et al.'s methodology [START_REF] Avikal | An AHP and PROMETHEE methods-based environment friendly heuristic for disassembly line balancing problems[END_REF] by using fuzzy AHP instead of AHP.

Tuzkaya et al. [START_REF] Tuzkaya | Environmental performance evaluation of suppliers: a hybrid fuzzy multi criteria decision approach[END_REF] evaluate the environmental performance of suppliers by developing a methodology that integrates fuzzy ANP and Fuzzy PROMETHEE.

Multi attribute utility theory (MAUT)

In multi attribute utility theory, decision maker represents a complex problem as a simple hierarchy and subjectively evaluates a large number of quantitative and qualitative factors considering risk and uncertainty. It can be used in both deterministic and stochastic decision environments [START_REF]International supplier selection: a multi-attribute utility approach[END_REF].

Erol et al. [START_REF] Erol | A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain[END_REF] integrate fuzzy entropy and fuzzy multiattribute utility (FMAUT) to measure the sustainability performance of a supply chain. First, fuzzy entropy method is used to determine the importance levels for the indicators. Then, fuzzy MAUT is utilized to calculate the aggregated performance indices with respect to each aspect of sustainability. Shaik and Abdul-Kader [START_REF] Shaik | Green supplier selection generic framework: a multi-attribute utility theory approach[END_REF] present use MAUT to develop an integrated and comprehensive framework for green supplier selection by considering traditional aspects as well as the environmental and the social factors.

VIKOR

VIKOR (VlseKriterijumskaOptimizacija I KompromisnoResenje (in Serbian), which means multi-criteria optimization and compromise solution) method determines the compromise ranking-list, the compromise solution, and the weight stability intervals for preference stability of the compromise solution obtained with the initial (given) weights. It is especially useful when there are conflicting criteria in the decision problem [START_REF] Opricovic | Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS[END_REF].

Rao [START_REF] Rao | An improved compromise ranking method for evaluation of environmentally conscious manufacturing programs[END_REF] proposes a VIKOR-based methodology for the selection of environmentally conscious manufacturing programs.

The green supplier selection and evaluation methodology developed by Datta et al. [START_REF] Datta | Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with intervalvalued fuzzy numbers[END_REF] integrates VIKOR with an interval-valued fuzzy set. Samantra et al. [START_REF] Samantra | Decision-making in selecting reverse logistics alternative using interval-valued fuzzy sets combined with VIKOR approach[END_REF] use the methodology proposed in Datta et al. [START_REF] Datta | Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with intervalvalued fuzzy numbers[END_REF] to determine the best product recovery option.

Sasikumar and Haq [START_REF] Sasikumar | Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling[END_REF] propose a two-step methodology for the design of a closed-loop supply chain. First, VIKOR is used to select the best third-party reverse logistics provider (3PRLP). Then, a mixed integer linear programming model is developed to make decisions on raw material procurement, production and distribution.

MACBETH

MACBETH (Measuring Attractiveness by a Categorical Based

Evaluation Technique) is a technique similar to AHP. The only difference is that MACBETH uses an interval scale while AHP adopts a ratio scale [START_REF] Ishizaka | Multi-criteria decision analysis: methods and software[END_REF].

Dhouib [START_REF] Dhouib | An extension of MACBETH method for a fuzzy environment to analyze alternatives in reverse logistics for automobile tire wastes[END_REF] proposes a fuzzy MACBETH methodology to evaluate options in reverse logistics for waste automobiles tires.

Case based reasoning

Case based reasoning is based on a memory-centered cognitive model. In this method, a reasoner remembers a previous situation similar to the current one and uses that to solve the new problem [START_REF] Xu | Case based reasoning[END_REF][START_REF] Kolodner | An introduction to case-based reasoning[END_REF].

Zeid et al. [START_REF] Zeid | A case-based reasoning approach to planning for disassembly[END_REF] present a CBR-based methodology to determine the disassembly plan of a single product. Extending Zeid et al. [START_REF] Zeid | A case-based reasoning approach to planning for disassembly[END_REF], Gupta and Veerakamolmal [START_REF] Gupta | A case-based reasoning approach for optimal planning of multi-product/multi-manufacturer disassembly processes[END_REF] and Veerakamolmal and Gupta [START_REF] Veerakamolmal | A case-based reasoning approach for automating disassembly process planning[END_REF] develop CBR approaches to automaticaly generate disassembly plans for multiple products.

Humphreys et al. [START_REF] Humphreys | Using case-based reasoning to evaluate supplier environmental management performance[END_REF] consider environmental factors in supplier selection process by developing a knowledge-based system (KBS) which integrates case-based reasoning (CBR) and decision support components.

Kuo [START_REF] Kuo | Combination of case-based reasoning and analytical hierarchy process for providing intelligent decision support for product recycling strategies[END_REF] integrates AHP and CBR to simplify the calculation of recyclability index which is used to evaluate the recyclability of an EOL product. Ghazalli and Murata [START_REF] Ghazalli | Development of an AHP-CBR evaluation system for remanufacturing: end-of-life selection strategy[END_REF] integrate AHP and CBR to evaluate EOL options for parts and components.

Gray relational analysis

In gray relational analysis, simple mathematical relations are used to deal with uncertain, poor and incomplete information. It solves multi attribute decision making problems by combining the entire range of performance attribute values being considered for every alternative into one, single value [START_REF] Kuo | The use of grey relational analysis in solving multiple attribute decision-making problems[END_REF].

Chan [START_REF] Chan | Product end-of-life options selection: grey relational analysis approach[END_REF] employs gray relational analysis to rank the product EOL options under uncertainty with respect to several criteria at the material level. Li and Zhao [START_REF] Li | Selection of suppliers of vehicle components based on green supply chain[END_REF] integrate threshold method and the gray correlation analysis for the selection of green suppliers. In Chen et al. [START_REF] Chen | Implementation of green supply chain management in uncertainty[END_REF], fuzzy logic and gray relational analysis are integrated to determine suitable suppliers by considering various environment-related criteria.

In Dou et al. [START_REF] Dou | Evaluating green supplier development programs with a grey-analytical network process-based methodology[END_REF], analytical network process and gray relational analysis are integrated to determine effective green supplier development programs.

Other techniques

Zareinejad and Javanmard [START_REF] Zareinejad | Evaluation and selection of a third-party reverse logistics provider using ANP and IFG-MCDM methodology[END_REF] develop an integrated methodology for third-party reverse logistics provider selection. First, relationships among the attributes are analyzed using analytic network process (ANP). Then, intuitionistic fuzzy set (IFS) and gray relation analysis (GRA) are integrated in order to determine the most suitable third party reverse logistics provider under uncertain conditions.

Hsu et al. [START_REF] Hsu | Using the FDM and ANP to construct a sustainability balanced scorecard for the semiconductor industry[END_REF] develop a balanced score card to measure the sustainable performance in semiconductor industry. Fuzzy Delphi method and ANP are used to identify the related measures and perspectives of sustainable balanced score card activities.

Hsu et al. [START_REF] Hsu | The best vendor selection for conducting the recycled material based on a hybrid MCDM model combining DANP with VIKOR[END_REF] combine DEMATEL, ANP and VIKOR to solve the recycled material vendor selection problem. First, DEMATEL and ANP are integrated to determine the degrees of influence among the criteria. Then, VIKOR is employed to rank the alternative vendors.

Yang and Wu [START_REF] Yang | Grey entropy method for green supplier selection[END_REF] employ gray entropy method for green supplier selection problem while Yu-zhong and Li-yun [START_REF]Extension method for green supplier selection[END_REF] solve the same problem using extension method based on entropy weight. Humphreys et al. [START_REF] Humphreys | Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process[END_REF] use dynamic fuzzy membership functions to select green supplies. Feyzioglu and Büyüközkan [START_REF] Feyzioglu | Evaluation of green suppliers considering decision criteria dependencies[END_REF] employ 2-additive Choquet integral to consider criteria dependencies in green supplier evaluation.

Rao and Padmanabhan [START_REF] Rao | Selection of best product end-of-life scenario using digraph and matrix methods[END_REF] use digraph and matrix methods for the selection of best product end-of-life scenario. Bereketli et al. [START_REF] Bereketli | WEEE treatment strategies' evaluation using fuzzy LINMAP method[END_REF] evaluate alternative waste treatment strategies for electrical and electronic equipments using fuzzy LINMAP (linear programming technique for multidimensional analysis of preference). Iakovou et al. [START_REF] Iakovou | A methodological framework for end-of-life management of electronic products[END_REF] develop a multi-criteria analysis technique called multi-criteria matrix to rank components according to their potential value at the end of their useful life. In Lee et al. [START_REF] Lee | A multi-objective methodology for evaluating product end-of-life options and disassembly[END_REF], a multi objective methodology has been developed to determine an appropriate end-of-life option for a product based on the minimization of environmental impact and the costs associated with collection, recovery (e.g., remanufacturing, recycling) and disposal. Sangwan [START_REF] Sangwan | Evaluation of manufacturing systems based on environmental aspects using a multi-criteria decision model[END_REF] develop a multi-criteria performance analysis tool to evaluate the performance of manufacturing systems based on environmental criteria. Mangla et al. [START_REF] Mangla | Multi-objective decision modelling using interpretive structural modelling for green supply chains[END_REF] use interpretive structural modeling to analyze the interaction among the various green supply chain enablers/barriers (e.g., supplier commitment, cost, regulations).

Integration of multi-objective optimization techniques with multi-criteria analysis

This section presents an overview of the studies which integrate the multi-objective optimization techniques with multi-criteria analysis.

Walther et al. [START_REF] Walther | Planning and evaluation of sustainable reverse logistics systems[END_REF] present a two-step methodology for the evaluation of alternative scrap treatment systems. First, linear programming or weighted goal programming is used to determine short-term decisions. Then, the results obtained in the first step are used as a priori information for multi-criteria decision making tool, PROMETHEE at strategic level.

Nukala and Gupta [START_REF] Nukala | Supplier selection in a closed-loop supply chain network: an ANP-goal programming based methodology[END_REF] employ ANP-GP integration for the supplier selection problem of a closed-loop supply chain. First, the supply chain strategy is determined qualitatively by evaluating the suppliers with respect to several criteria. Then preemptive goal programming taking ANP ratings as input is used to determine the optimal quantities to be ordered from the suppliers.

In Ravi et al. [START_REF] Ravi | Selection of a reverse logistics project for end-of-life computers: ANP and goal programing approach[END_REF], an integrated ANP-GP methodology is used to select reverse logistics projects. Following the determination of the level of interdependence among the criteria and candidate reverse logistics projects using ANP, zero-one goal programming determines the allocation of resources among reverse logistics projects by considering resource limitations and several other selection constraints.

Dehghanian and Mansour [START_REF] Dehghanian | Designing sustainable recovery network of end-of-life products using genetic algorithm[END_REF] integrate AHP and genetic algorithms for the recovery network design of scrap tires. In the proposed methodology, first, AHP is used to calculate social impacts. Then the Pareto-optimal solutions are determined by using a multi-objective genetic algorithm (MOGA).

Vadde et al. [START_REF] Vadde | Pricing decisions in a multi-criteria setting for product recovery facilities[END_REF] analyze the pricing decisions of product recovery facilities by integrating multi-objective mathematical programming, genetic algorithms and AHP. The weights used in the objective function of the genetic algorithm designed to solve the multi-objective mathematical programming model are determined using AHP. Ge [START_REF] Ge | Research on green suppliers' evaluation based on AHP & genetic algorithm[END_REF] integrates GA and AHP for the evaluation of green suppliers.

Pochampally and Gupta [START_REF] Pochampally | A multiphase fuzzy logic approach to strategic planning of a reverse supply chain network[END_REF] develop a three-phase methodology for the effective design of a reverse supply chain network. The most economical product to reprocess from a set of different used products is selected in phase 1 using a fuzzy benefit function. AHP and fuzzy set theory are employed in phase 2 to identify potential facilities in a set of candidate recovery facilities. Phase III solves a single-period and single-product discrete location model to minimize overall cost across the reverse supply chain network.

Nukala and Gupta [START_REF] Nukala | A fuzzy mathematical programming approach for supplier selection in a closed-loop supply chain network[END_REF] integrate Taguchi loss functions, AHP and fuzzy programming to evaluate the suppliers and determine the order quantities in a closed-loop supply chain network. First, Taguchi loss functions quantify the suppliers attributes to quality loss. Then AHP is used to transform these quality losses into a variable that is used in the formulation of the fuzzy programming objective function. Finally, fuzzy programming determines the order quantities.

Buyukozkan and Berkol [START_REF] Buyukozkan | Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment[END_REF] integrate ANP, goal programming and quality function deployment to design a sustainable supply chain. ANP is employed to determine the importance levels in the house of qualiy by considering the interrelationships among the design requirements and customer requirements while zeroone goal programming is used to select the most suitable design requirements based on ANP results.

Paksoy et al. [START_REF] Paksoy | Fuzzy multi-objective optimization of a green supply chain network with risk management that includes environmental hazards[END_REF] first propose a fuzzy programming model with multiple objectives for the design of a closed-loop supply chain network. Then, various multi criteria techniques (viz., AHP, fuzzy AHP and fuzzy TOPSIS) are applied to weight the objectives and the corresponding results are discussed.

Kannan et al. [START_REF] Kannan | Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain[END_REF] propose an integrated approach for supplier selection and order allocation in a green supply chain. First, the relative weights of supplier selection criteria are calculated using fuzzy AHP; then, fuzzy TOPSIS is employed to rank suppliers based on the selected criteria. Finally, MOLP model determines the optimal order quantity from each supplier using the weights of the criteria and ranks of suppliers.

Conclusions

In this paper, we presented a review of the state of the art literature on the use of multi-criteria decision making techniques in environmentally conscious manufacturing and product recovery (ECMPRO). The MCDM techniques were presented by category, i.e.; multi-objective optimization, multi-criteria analysis and the integration between them. The following general conclusions can be drawn from our literature review.

Since ECMPRO initiatives have economic and environmental consequences, majority of the studies simultaneously consider economic and environmental criteria. The most commonly used environmental criteria include green product design, reduction of material and energy use, use of environment friendly technology, pollution control, environmental management system, green purchasing, green packaging and hazardous substance management system.

There is a significant increase in the number of publications concerning the use of MCDM techniques for ECMPRO problems in recent years. This can be attributed to the increasing popularity of environmental issues among researchers.

Multi-criteria analysis is more popular than multi-objective optimization in ECMPRO. Among the most frequently used techniques, one can find AHP, ANP and TOPSIS. On the other hand, the use of other techniques as MACBETH, DEMATEL, ELECTRE, PROMETHEE is surprisingly rare.

Although simulation is very good at modeling complex systems, its integration with MCDM techniques for the solution of ECM-PRO related problems is limited to a few studies. Hence, there are opportunities to develop multi objective solution methodologies integrating simulation with qualitative and/or quantitative MCDM techniques to solve complex ECMPRO issues such as disassembly planning, reverse logistics and CLSC design.

Fig. 1 .

 1 Fig. 1. Closed-loop supply chain.