Abstract
Abstract. Closed loop supply chain (CLSC) optimization is integration of forward and reverse logistics activities. The importance of CLSC management is increasing by legal regulations, limited energy resources and environmental- financial problems that growing in recent years. However, reverse logistics part of the CLSC is a flow type which is more difficult to made predictions, planning and controls by reason contained uncertainties. This stage, Internet of Things system reduces related uncertainties by providing all the life information of the returned product and substantially attenuates planning of reverse flow activities. In this study, a CLSC is considered that meets demands of the sales&collection center both new and remanufactured product. Manufacturer has three options (refurbishing, disassembly and disposal) to assessing returned products. A mixed integer linear programming model is proposed for a single type of product is completely modular (automobile, computer, telephone, etc.). The model meets customer's products and components demands based period, maximizes profit consist of different sales revenues and total cost (total production, purchase, transportation and disposal costs) and determines how to evaluate all returned products. The proposed model has been verified with the aid of a numerical example by solving in GAMS software and its performance reviewed with experimental studies.
Keywords. Closed loop supply chain optimization, Internet of Things, Mixedinteger linear programming, Returned product management.
JEL. L80, L86, Q55.
References
Akçalı, E., & Cetinkaya, S. (2011). Quantitative models for inventory and production planning in closed-loop supply chains. International Journal of Production Research, 49(8), 2373-2407. doi. 10.1080/00207541003692021
Amin, S.H., & Zhang, G. (2013). A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 37(6), 4165-4176. doi. 10.1016/j.apm.2012.09.039
Beamon, B.M., & Fernandes, C. (2004). Supply-chain network configuration for product recovery. Production Planning & Control, 15(3), 270-281. doi. 10.1080/09537280410001697701
Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J.M., & Wassenhove, L.N. (2001). The impact of product recovery on logistics network design. Production and Operations Management, 10(2), 156-173. doi. 10.1111/j.1937-5956.2001.tb00076.x
Fleischmann, M., Bloemhof-Ruwaard, J.M., Dekker, R., Van der Laan, E., Van Nunen, J.A., & Van Wassenhove, L.N. (1997). Quantitative models for reverse logistics: A review. European Journal of Operational Research, 103(1), 1-17. doi. 10.1016/S0377-2217(97)00230-0
Govindan, K., Soleimani, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240(3), 603-626. doi. 10.1016/j.ejor.2014.07.012
Gu, Y., & Liu, Q. (2013). Research on the application of the internet of things in reverse logistics information management. Journal of Industrial Engineering and Management, 6(4), 963-973. doi. 10.3926/jiem.793
Guide Jr, V.D.R., & Van Wassenhove, L.N. (2009). OR FORUM-the evolution of closed-loop supply chain research. Operations research, 57(1), 10-18. doi. 10.1287/opre.1080.0628
Guide, V.D.R., Jayaraman, V., & Linton, J.D. (2003). Building contingency planning for closed-loop supply chains with product recovery. Journal of Operations Management, 21(3), 259-279. doi. 10.1016/S0272-6963(02)00110-9
Gupta, A., & Evans, G.W. (2009). A goal programming model for the operation of closed-loop supply chains. Engineering Optimization, 41(8), 713-735. doi. 10.1080/03052150902802242
Ilgin, M.A., & Gupta, S.M. (2011). Performance improvement potential of sensor embedded products in environmental supply chains. Resources, Conservation and Recycling, 55(6), 580-592. doi. 10.1016/j.resconrec.2010.05.001
Jayaraman, V. (2006). Production planning for closed-loop supply chains with product recovery and reuse: an analytical approach. International Journal of Production Research, 44(5), 981-998. doi. 10.1080/00207540500250507
Jindal, A., & Sangwan, K.S. (2014). Closed loop supply chain network design and optimisation using fuzzy mixed integer linear programming model. International Journal of Production Research, 52(14), 4156-4173. doi. 10.1080/00207543.2013.861948
Jun, H.B., Kiritsis, D., & Xirouchakis, P. (2007). Research issues on closed-loop PLM. Computers in industry, 58(8), 855-868. doi. 10.1016/j.compind.2007.04.001
Kannan, G., Sasikumar, P., & Devika, K. (2010). A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling. Applied Mathematical Modelling, 34(3), 655-670. doi. 10.1016/j.apm.2009.06.021
Kiritsis, D. (2011). Closed-loop PLM for intelligent products in the era of the Internet of things. Computer-Aided Design, 43(5), 479-501. doi. 10.1016/j.cad.2010.03.002
Krikke, H., Bloemhof-Ruwaard, J., & Van Wassenhove, L.N. (2001). Design of closed loop supply chains: a production and return network for refrigerators. Rotterdam, The Netherlands: Erasmus Research Institute of Management (ERIM).
Kumar, S., & Craig, S. (2007). Dell, Inc.'s closed loop supply chain for computer assembly plants. Information-Knowledge-Systems Management, 6(3), 197-214.
Kutup, N. (2011). NesnelerinInterneti; 4H Her yerden, Herkesle, Her zaman, Hernesneilebağlantı. 16. Türkiye’de İnternet Konferansı inet-tr’11.
Min, H., Ko, C.S., &Ko, H.J. (2006). The spatial and temporal consolidation of returned products in a closed-loop supply chain network. Computers & Industrial Engineering, 51(2), 309-320. doi. 10.1016/j.cie.2006.02.010
Ondemir, O., & Gupta, S.M. (2014a). A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system. European Journal of Operational Research, 233(2), 408-419. doi. 10.1016/j.ejor.2013.09.003
Ondemir, O., & Gupta, S. M. (2014b). Quality management in product recovery using the Internet of Things: An optimization approach. Computers in Industry, 65(3), 491-504. doi. 10.1016/j.compind.2013.11.006
Ondemir, O., Ilgin, M.A., & Gupta, S.M. (2012). Optimal end-of-life management in closed-loop supply chains using RFID and sensors. Industrial Informatics, IEEE Transactions on, 8(3), 719-728. doi. 10.1109/TII.2011.2166767
Özceylan, E. (2013). Demontaj hattı dengeleme problem içeren kapalı çevrim tedarik zincirlerinin bulanık ortamda modellenmesi ve optimizasyonu (Doctoral dissertation, Selçuk Üniversitesi Fen Bilimleri Enstitüsü).
Özceylan, E., & Paksoy, T. (2013a). A mixed integer programming model for a closed-loop supply-chain network. International Journal of Production Research, 51(3), 718-734. doi. 10.1080/00207543.2012.661090
Özceylan, E., & Paksoy, T. (2013b). Fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network. International Journal of Production Research, 51(8), 2443-2461. doi. 10.1080/00207543.2012.740579
Özceylan, E., Paksoy, T., & Bektaş, T. (2014). Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing. Transportation Research Part E: Logistics and Transportation Review, 61, 142-164. doi. 10.1016/j.tre.2013.11.001
Pagell, M., Wu, Z., & Murthy, N.N. (2007). The supply chain implications of recycling. Business Horizons, 50(2), 133-143. doi. 10.1016/j.bushor.2006.08.007
Paksoy, T., Bektaş, T., & Özceylan, E. (2011). Operational and environmental performance measures in a multi-product closed-loop supply chain. Transportation Research Part E: Logistics and Transportation Review, 47(4), 532-546. doi. 10.1016/j.tre.2010.12.001
Pazhani, S., Ramkumar, N., Narendran, T.T., & Ganesh, K. (2013). A bi-objective network design model for multi-period, multi-product closed-loop supply chain. Journal of Industrial and Production Engineering, 30(4), 264-280. doi. 10.1080/21681015.2013.830648
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. doi. 10.1016/j.fss.2010.04.010
Ramezani, M., Kimiagari, A.M., Karimi, B., & Hejazi, T.H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems, 59, 108-120. doi. 10.1016/j.knosys.2014.01.016
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. doi. 10.1016/j.ejor.2005.05.032
Salema, M.I.G., Póvoa, A.P.B., & Novais, A.Q. (2009). A strategic and tactical model for closed-loop supply chains. OR spectrum, 31(3), 573-599. doi. 10.1007/s00291-008-0160-5
Sheu, J.B., Chou, Y.H., & Hu, C.C. (2005). An integrated logistics operational model for green-supply chain management. Transportation Research Part E: Logistics and Transportation Review, 41(4), 287-313. doi. 10.1016/j.tre.2006.04.004
Visich, J.K., Li, S., & Khumawala, B.M. (2007). Enhancing product recovery value in closed-loop supply chains with RFID. Journal of Managerial Issues, 19(3), 436-452.
Yang, G.F., Wang, Z.P., & Li, X.Q. (2009). The optimization of the closed-loop supply chain network. Transportation Research Part E: Logistics and Transportation Review, 45(1), 16-28. doi. 10.1016/j.tre.2008.02.007
Zeballos, L.J., Gomes, M.I., Barbosa-Povoa, A.P., & Novais, A.Q. (2012). Addressing the uncertain quality and quantity of returns in closed-loop supply chains. Computers & Chemical Engineering, 47, 237-247. doi. 10.1016/j.compchemeng.2012.06.034
Zeballos, L.J., Méndez, C.A., Barbosa-Povoa, A.P., & Novais, A.Q. (2014). Multi-period design and planning of closed-loop supply chains with uncertain supply and demand. Computers & Chemical Engineering, 66, 151-164. doi. 10.1016/j.compchemeng.2014.02.027
Zhiduan, X. (2005). Research on the Flexibility in Logistic Systems. Chinese Journal of Management, 4, 441-445.
