An Integrated Approach for Collection Center Selection in Reverse Logistics


1 Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran

2 Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran


In this paper, a hybrid multi-criteria decision-making (MCDM)-method and mixed integer linear programming (MILP) approach in order to evaluation of the returned products' collectors along with their ordered quantities, is utilized. Firstly, the most important criteria of collection center in the car industry are identified. Then, in order to evaluate these proposed criteria, a hybrid Fuzzy Decision-Making Trial And Evaluation Laboratory (FDEMATEL)- evaluation of mixed qualitative and quantitative data (EVAMIX) approach is applied. By this method, the most important criteria and their weights along with collection centers' score are determined. In addition, an MILP mathematical model is proposed for selection of the best collection center and computation of ordering quantities. An efficient approach for collection center selection and a novel application of combined FDEMATEL, EVAMIX, and MILP model can be considered as the main contributions of this paper. It should be noted that, to measure the performance of this method a recycling company as a case study in Iran has considered which of this firm collects effete tire and ball bearings of cars. Implementation of this case study can be considered as the other contributions of this paper. At last, with help of obtained results the proper collection center and their ordered quantities are computed. In addition, for measure efficiency of the proposed model, some numerical example, in various dimensions is considered. Moreover, the managers of this industry with the help of a simple methodology can choose the appropriate suppliers.


1.     Barros, A.I., Dekker, R. and Scholten, V., "A two-level network for recycling sand: A case study", European Journal of Operational Research,  Vol. 110, No. 2, (1998), 199-214.

2.     Jayaraman, V. and Luo, Y., "Creating competitive advantages through new value creation: A reverse logistics perspective", The Academy of Management Perspectives,  Vol. 21, No. 2, (2007), 56-73.

3.     Amin, S.H., Zhang, G. and Akhtar, P., "Effects of uncertainty on a tire closed-loop supply chain network", Expert Systems with Applications,  Vol. 73, No., (2017), 82-91.

4.     de Souza, C.D.R. and Márcio de Almeida, D.A., "Value chain analysis applied to the scrap tire reverse logistics chain: An applied study of co-processing in the cement industry", Resources, Conservation and Recycling,  Vol. 78, (2013), 15-25.

5.     Dhouib, D., "An extension of macbeth method for a fuzzy environment to analyze alternatives in reverse logistics for automobile tire wastes", Omega,  Vol. 42, No. 1, (2014), 25-32.

6.     Krikke, H., Hofenk, D. and Wang, Y., "Revealing an invisible giant: A comprehensive survey into return practices within original (closed-loop) supply chains", Resources, Conservation and Recycling,  Vol. 73, (2013), 239-250.

7.     Carter, C.R. and Ellram, L.M., "Reverse logistics: A review of the literature and framework for future investigation", Journal of Business Logistics,  Vol. 19, No. 1, (1998), 85-92.

8.     Prakash, C. and Barua, M., "Integration of ahp-topsis method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment", Journal of Manufacturing Systems,  Vol. 37, (2015), 599-615.

9.     Fleischmann, M., Krikke, H.R., Dekker, R. and Flapper, S.D.P., "A characterisation of logistics networks for product recovery", Omega,  Vol. 28, No. 6, (2000), 653-666.

10.   Jayaraman, V., Patterson, R.A. and Rolland, E., "The design of reverse distribution networks: Models and solution procedures", European Journal of Operational Research,  Vol. 150, No. 1, (2003), 128-149.

11.   Srivastava, S.K., "Network design for reverse logistics", Omega,  Vol. 36, No. 4, (2008), 535-548.

12.   Lee, D.-H. and Dong, M., "A heuristic approach to logistics network design for end-of-lease computer products recovery", Transportation Research Part E: Logistics and Transportation Review,  Vol. 44, No. 3, (2008), 455-474.

13.   Ravi, V., Shankar, R. and Tiwari, M., "Analyzing alternatives in reverse logistics for end-of-life computers: Anp and balanced scorecard approach", Computers & Industrial Engineering,  Vol. 48, No. 2, (2005), 327-356.

14.   Rogers, D.S. and Tibben‐Lembke, R., "An examination of reverse logistics practices", Journal of Business Logistics,  Vol. 22, No. 2, (2001), 129-148.

15.   Blumberg, D.F., "Strategic examination of reverse logistics & repair service requirements, needs, market size, and opportunities", Journal of Business Logistics,  Vol. 20, No. 2, (1999), 141-150.

16.   Amini, M.M., Retzlaff-Roberts, D. and Bienstock, C.C., "Designing a reverse logistics operation for short cycle time repair services", International Journal of Production Economics,  Vol. 96, No. 3, (2005), 367-380.

17.   Krumwiede, D.W. and Sheu, C., "A model for reverse logistics entry by third-party providers", Omega,  Vol. 30, No. 5, (2002), 325-333.

18.   McCarthy, I.P., Silvestre, B.S. and Kietzmann, J.H., "Understanding outsourcing contexts through information asymmetry and capability fit", Production planning & control,  Vol. 24, No. 4-5, (2013), 277-283.

19.   Bruno, G., Esposito, E., Genovese, A. and Passaro, R., "Ahp-based approaches for supplier evaluation: Problems and perspectives", Journal of Purchasing and Supply Management,  Vol. 18, No. 3, (2012), 159-172.

20.   Buyukozkan, G. and Çifçi, G., "A novel hybrid mcdm approach based on fuzzy dematel, fuzzy anp and fuzzy topsis to evaluate green suppliers", Expert Systems with Applications,  Vol. 39, No. 3, (2012), 3000-3011.

21.   Pourebrahim, S., Hadipour, M., Mokhtar, M.B. and Taghavi, S., "Application of vikor and fuzzy ahp for conservation priority assessment in coastal areas: Case of khuzestan district, iran", Ocean & Coastal Management,  Vol. 98, (2014), 20-26.

22.   Eskandarpour, M. and Hasani, A., "Comprehensive decision modeling of reverse logistics system: A multi-criteria decision making model by using hybrid evidential reasoning approach and topsis", International Journal of Engineering-Transactions C: Aspects,  Vol. 28, No. 6, (2015), 922-930.

23.   Mousavi, S., Gitinavard, H. and Vahdani, B., "Evaluating construction projects by a new group decision-making model based on intuitionistic fuzzy logic concepts", International Journal of Engineering-Transactions C: Aspects,  Vol. 28, No. 9, (2015), 1312-1320.

24.   Sadjadi, S. and Bayati, M.F., "Two-tier supplier base efficiency evaluation via network dea: A game theory approach", International Journal of Engineering-Transactions A: Basics,  Vol. 29, No. 7, (2016), 931-940.

25.   Moubed, M. and Mehrjerdi, Y.Z., "A hybrid dynamic programming for inventory routing problem in collaborative reverse supply chains", International Journal of Engineering, TRANSACTIONS A: Basics,  Vol. 29, No. 10, (2016), 1412-1420.

26.   Soltani, R., Tofigh, A. and Sadjadi, S., "Redundancy allocation combined with supplier selection for design of series-parallel systems", International Journal of Engineering-Transactions B: Applications,  Vol. 28, No. 5, (2014), 730-738.

27.   Azadnia, A., "A multi-objective mathematical model for sustainable supplier selection and order lot-sizing under inflation", International Journal of Engineering-Transactions B: Applications,  Vol. 29, No. 8, (2016), 1141-1149.

28.   Kannan, G., Murugesan, P., Senthil, P. and Noorul Haq, A., "Multicriteria group decision making for the third party reverse logistics service provider in the supply chain model using fuzzy topsis for transportation services", International Journal of Services Technology and Management,  Vol. 11, No. 2, (2009), 162-181.

29.   Yang, J., Chen, J., Le, X. and Zhang, Q., "Density-oriented versus development-oriented transit investment: Decoding metro station location selection in shenzhen", Transport Policy,  Vol. 51, (2016), 93-102.

30.   Weiqing, Z., Donghao, P., Zhang, Y. and Xueshuang, L., "Location selection of deepwater relief wells in south china sea", Petroleum Exploration and Development,  Vol. 43, No. 2, (2016), 315-319.

31.   Chen, L.-F. and Tsai, C.-T., "Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain", Tourism Management,  Vol. 53, (2016), 197-206.

32.   Malik, S., Kumari, A. and Agrawal, S., "Selection of locations of collection centers for reverse logistics using gtma", Materials Today: Proceedings,  Vol. 2, No. 4-5, (2015), 2538-2547.

33.   Gabus, A. and Fontela, E., "The dematel observer", Battelle Geneva Research Center, Geneva, Switzerland, (1976).

34.   Patil, S.K. and Kant, R., "A hybrid approach based on fuzzy dematel and FMCDM to predict success of knowledge management adoption in supply chain", Applied Soft Computing,  Vol. 18, (2014), 126-135.

35.   Zadeh, L.A., "Fuzzy sets", Information and Control,  Vol. 8, No. 3, (1965), 338-353.

36.   Lin, C. and Wu, W.-W., "A fuzzy extension of the dematel method for group decision making",  (2004).

37.   Voogd, H., "Multicriteria evaluation with mixed qualitative and quantitative data", Environment and Planning B: Planning and Design,  Vol. 9, No. 2, (1982), 221-236.

38.   Martel, J.-M. and Matarazzo, B., "Other outranking approaches", Multiple Criteria Decision Analysis: State of the Art Surveys,  (2005), 197-259.

39.   Chen, S.-J., Hwang, C.-L. and Hwang, F.P., "Fuzzy multiple attribute decision making(methods and applications)", Lecture Notes in Economics and Mathematical Systems, (1992).