Multi-level optimization of an automotive closed-loop supply chain network with interactive fuzzy programming approaches
Abstract
Closed-Loop Supply Chain (CLSC) management has attained appreciable attention over the last few years. CLSC management allows companies to manage their recovery and recycling activities of end products. Due to the latest developments in the world, producers are responsible for the collection, refurbishing, repairing and disassembly of end products at the end of their lives. This paper develops a mixed-integer CLSC model that is inspired by the automotive industry. In this model, we consider three Decision Makers (DM): Plant, Dismantler Center and Customer. Each DM has individual objectives and is responsible for only its own objective function under same constraints. In order to tackle the trade-offs among the objectives, we used four different Interac-tive Fuzzy Programming (IFP) approaches. The applications of the model and solution techniques are investigated in conjectural data. The paper ends with a conclusion and a call for future studies.
Keyword : automotive industry, closed-loop supply chain, interactive fuzzy programming, multi- level programming, mixed-integer linear programming
How to Cite
Yildizbaşi, A., Çalik, A., Paksoy, T., Farahani, R. Z., & Weber, G.-W. (2018). Multi-level optimization of an automotive closed-loop supply chain network with interactive fuzzy programming approaches. Technological and Economic Development of Economy, 24(3), 1004-1028. https://doi.org/10.3846/20294913.2016.1253044
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Torabi, S. A.; Hassini, E. 2008. An interactive possibilistic programming approach for multiple objective supply chain master planning, Fuzzy Sets and Systems 159(2): 193–214. https://doi.org/10.1016/j.fss.2007.08.010
Vahdani, B.; Moghaddam, R. T.; Modarres, M.; Baboli, A. 2012. Reliable design of a forward/reverse logistics network under uncertainty: a robust-M/M/c queuing model, Transportation Research Part E: Logistics and Transportation Review 48(6): 1152–1168. https://doi.org/10.1016/j.tre.2012.06.002
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Wang, H.-F.; Hsu, H.-W. 2010. A closed-loop logistic model with a spanning-tree based genetic algorithm, Computers and Operations Research 37(2): 376–389. https://doi.org/10.1016/j.cor.2009.06.001
Williams, J. A. S.; Wongweragiat, S.; Qu, X.; McGlinch, J. B.; Bonawi-tan, W.; Choi, J. K.; Schiff, J. 2007. An automotive bulk recycling planning model, European Journal of Operational Research 177: 969–981. https://doi.org/10.1016/j.ejor.2006.01.031
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Zarei, M.; Mansour, S.; Kashan, A. H.; Karimi, B. 2010. Designing a reverse logistics network for end-of-life vehicles recovery, Mathematical Problems in Engineering. Article ID 649028.
Zhou, Y.; Xiong, Y.; Li, G., Xiong, Z.; Beck, M. 2013. The bright side of manufacturing-remanufacturing conflict in a decentralized closed-loop supply chain, International Journal of Production Research 51(9): 2639–2651. https://doi.org/10.1080/00207543.2012.737956
Zimmermann, H. J. 1978. Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems 1(1): 45–55. https://doi.org/10.1016/0165-0114(78)90031-3
Azevedo, S. G.; Carvalho, H.; Cruz, Machado, V. 2011. The influence of green practices on Supply Chain performance: a case study approach, Transportation Research Part E: Logistics and Transportation Review 47(6): 850–871. https://doi.org/10.1016/j.tre.2011.05.017
Baenas, J. M. H.; Castro, R. de.; Battistelle, R. A. G.; Junior, J. A. G. 2011. A study of reverse logistics flow management in vehicle battery industries in the Midwest of the state of São Paulo (Brazil), Journal of Cleaner Production 19(2–3): 168–172. https://doi.org/10.1016/j.jclepro.2010.08.018
Bilgen, B. 2010. Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem, Expert Systems with Applications 37(6): 4488–4495. https://doi.org/10.1016/j.eswa.2009.12.062
Cruz-Rivera, R.; Ertel, J. 2009. Reverse logistics network design for the collection of end-of-life vehicles in Mexico, European Journal of Operational Research 196: 930–939. https://doi.org/10.1016/j.ejor.2008.04.041
Demirel, N. Ö.; Gökçen, H. 2008. A mixed integer programming model for remanufacturing in reverse logistics environment, The International Journal of Advanced Manufacturing Technology 39(11–12): 1197–1206. https://doi.org/10.1007/s00170-007-1290-7
Farahani, R. Z.; Rezapour, S.; Drezner, T.; Fallah, S. 2014. Competitive supply chain network design: an overview of classifications, models, solution techniques and applications, Omega 45: 92–118. https://doi.org/10.1016/j.omega.2013.08.006
Harraz, N. A.; Galal, N. M. 2011. Design of sustainable end-of-life vehicle recovery network in Egypt, Ain Shams Engineering Journal 2(3–4): 211–219. https://doi.org/10.1016/j.asej.2011.09.006
Kanari, N.; Pineau, J-L.; Shallari, S. 2003. End-of-life vehicle recycling in the European Union [online], [cited 05 January 2015]. Available from Internet: http://www.tms.org/pubs/journals/JOM/0308/Kanari-0308.html
Kumar, V.; Sutherland, J.-W. 2008. Sustainability of the automotive recycling infrastructure: review of current research and identification of future challenges, International Journal of Sustainable Manufacturing 1(1/2): 145–167. https://doi.org/10.1504/IJSM.2008.019231
Liang, T. F. 2006. Distribution planning decisions using interactive fuzzy multi-objective linear programming, Fuzzy Sets and Systems 157(10): 1303–1316. https://doi.org/10.1016/j.fss.2006.01.014
Mahmoudzadeh, M.; Mansour, S.; Karimi, B. 2013. To develop a third-party reverse logistics network for end-of-life vehicles in Iran, Resources, Conservation and Recycling 78: 1–14. https://doi.org/10.1016/j.resconrec.2013.06.006
Mirakhorli, A. 2014. Fuzzy multi-objective optimization for closed loop logistics network design in bread-producing industries, International Journal of Advanced Manufacturing Technology 70: 349–362. https://doi.org/10.1007/s00170-013-5264-7
Neto, J. Q. F.; Bloemhof-Ruwaard, J. M.; Van Nunen, J. A. E. E.; Van Heck, E. 2008. Designing and evaluating sustainable logistics networks, International Journal of Production Economics 111(2): 195–208. https://doi.org/10.1016/j.ijpe.2006.10.014
Özceylan, E.; Paksoy, T. 2012. A mixed integer programming model for a closed-loop supply chain network, International Journal of Production Research 51(3): 718–734. https://doi.org/10.1080/00207543.2012.661090
Özceylan, E.; Paksoy, T.; Bektaş, T. 2014. Modeling and optimizing the integrated problem of closedloop supply chain network design and disassembly line balancing, Transportation Research Part E 6: 142–164. https://doi.org/10.1016/j.tre.2013.11.001
Paksoy, T.; Özceylan, E. 2013. An interactive fuzzy programming approach for a decentralized closedloop supply chain network design problem, in 26th European Conference on Operational Conference, 1–3 July 2013, Rome, Italy, Abstract book: 65.
Pishvaee, M. S.; Torabi, S. A. 2010. A possibilistic programming approach for closed-loop supply chain network design under uncertainty, Fuzzy Sets and Systems 161(20): 2668–2683. https://doi.org/10.1016/j.fss.2010.04.010
Qu, X.; Williams, J. A. S. 2008. An analytical model for reverse automotive production planning and pricing, European Journal of Operational Research 190: 756–767. https://doi.org/10.1016/j.ejor.2007.06.041
Sakawa, M.; Nishizaki, I. 2002. Interactive fuzzy programming for decentralized two-level linear programming problems, Fuzzy Sets and Systems 125(3): 301–315. https://doi.org/10.1016/S0165-0114(01)00042-2
Sakawa, M.; Nishizaki, I.; Uemura, Y. 1998. Interactive fuzzy programming for multilevel linear programming problems, Computers & Mathematics with Applications 36(2): 71–86. https://doi.org/10.1016/S0898-1221(98)00118-7
Salema, M. I. G.; Barbosa-Povoa, A. P.; Novais, A. Q. 2007. An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty, European Journal of Operational Research 179(3): 1063–1077. https://doi.org/10.1016/j.ejor.2005.05.032
Sasikumar, P.; Haq, A. N. 2010. Analysing interactions among battery recycling barriers in the reverse supply chain, in L. Wang, S. Koh (Eds.). Enterprise Networks and Logistics for Agile Manufacturing. Springer, London, 249–269. https://doi.org/10.1007/978-1-84996-244-5_12
Schultmann, F.; Zumkeller, M.; Rentz, O. 2006. Modelling reverse logistic tasks within closed-loop supply chains: an example from the automotive industry, European Journal of Operational Research 171(3): 1033–1050. https://doi.org/10.1016/j.ejor.2005.01.016
Selim, H.; Araz, C.; Özkarahan, I. 2008. Collaborative production–distribution planning in supply chain: a fuzzy goal programming approach, Transportation Research Part E 44(3): 396–419. https://doi.org/10.1016/j.tre.2006.11.001
Selim, H.; Ozkarahan, İ. 2008. A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach, International Journal of Advanced Manufacturing Technology 36(3–4): 401–418. https://doi.org/10.1007/s00170-006-0842-6
Staudinger, J.; Keoleian, G. A.; Flynn, M. S. 2001. Management of end-of-life vehicles (ELVs) in the US. Report for Japan External Trade Organization (JETRO), University of Michigan Centre for Sustainable Systems Report No CSS01-01 Ann Arbor MI.
Subulan, K.; Tasan, A. S.; Baykasoğlu, A. 2015a. A fuzzy goal programming model to strategic planning problem of a lead/acid battery closed-loop supply chain, Journal of Manufacturing Systems 37 Part 1: 243–264. https://doi.org/10.1016/j.jmsy.2014.09.001
Subulan, K.; Tasan, A. S.; Baykasoğlu, A. 2015b. Designing an environmentally conscious tire closedloop supply chain network with multiple recovery options using interactive fuzzy goal programming, Applied Mathematical Modelling 39(9): 2661–2702. https://doi.org/10.1016/j.apm.2014.11.004
Tang, Q.; Xie, F. 2007. A genetic algorithm for reverse logistics network design, in ICNC ‘07 Proceedings of the Third International Conference on Natural Computation, 24–27 August 2007, 4: 277–281.
Torabi, S. A.; Hassini, E. 2008. An interactive possibilistic programming approach for multiple objective supply chain master planning, Fuzzy Sets and Systems 159(2): 193–214. https://doi.org/10.1016/j.fss.2007.08.010
Vahdani, B.; Moghaddam, R. T.; Modarres, M.; Baboli, A. 2012. Reliable design of a forward/reverse logistics network under uncertainty: a robust-M/M/c queuing model, Transportation Research Part E: Logistics and Transportation Review 48(6): 1152–1168. https://doi.org/10.1016/j.tre.2012.06.002
Vidovic, M.; Dimitrijevic, B.; Ratkovic, B.; Simic, V. 2011. A novel covering approach to positioning ELV collection points, Resources, Conservation and Recycling 57: 1–9. https://doi.org/10.1016/j.resconrec.2011.09.013
Wang, H.-F.; Hsu, H.-W. 2010. A closed-loop logistic model with a spanning-tree based genetic algorithm, Computers and Operations Research 37(2): 376–389. https://doi.org/10.1016/j.cor.2009.06.001
Williams, J. A. S.; Wongweragiat, S.; Qu, X.; McGlinch, J. B.; Bonawi-tan, W.; Choi, J. K.; Schiff, J. 2007. An automotive bulk recycling planning model, European Journal of Operational Research 177: 969–981. https://doi.org/10.1016/j.ejor.2006.01.031
Zarandi, M. H.; Sisakht, A. H.; Davari, S. 2011. Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming, The International Journal of Advanced Manufacturing Technology 56(5): 809–821. https://doi.org/10.1007/s00170-011-3212-y
Zarei, M.; Mansour, S.; Kashan, A. H.; Karimi, B. 2010. Designing a reverse logistics network for end-of-life vehicles recovery, Mathematical Problems in Engineering. Article ID 649028.
Zhou, Y.; Xiong, Y.; Li, G., Xiong, Z.; Beck, M. 2013. The bright side of manufacturing-remanufacturing conflict in a decentralized closed-loop supply chain, International Journal of Production Research 51(9): 2639–2651. https://doi.org/10.1080/00207543.2012.737956
Zimmermann, H. J. 1978. Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems 1(1): 45–55. https://doi.org/10.1016/0165-0114(78)90031-3