A Comprehensive Mathematical Programming Model for Minimizing Costs in a Multiple-Item Reverse Supply Chain with Sensitivity Analysis

• Autorzy: Hoda Mahmoudi , Hamed Fazlollahtabar
• Języki publikacji: EN

Abstrakty

EN

These instructions give you guidelines for preparing papers for IFAC conferences. A reverse supply chain is configured by a sequence of elements forming a continuous process to treat return-products until they are properly recovered or disposed. The activities in a reverse supply chain include collection, cleaning, disassembly, test and sorting, storage, transport, and recovery operations. This paper presents a mathematical programming model with the objective of minimizing the total costs of reverse supply chain including transportation, fixed opening, operation, maintenance and remanufacturing costs of centers. The proposed model considers the design of a multi-layer, multi-product reverse supply chain that consists of returning, disassembly, processing, recycling, remanufacturing, materials and distribution centers. This integer linear programming model is solved by using Lingo 9 software and the results are reported. Finally, a sensitivity analysis of the proposed model is also presented. (original abstract)

Słowa kluczowe

EN

Mathematical programming; Mathematical modeling; Sensitivity analysis; Supply chain

PL

Programowanie matematyczne; Modelowanie matematyczne; Analiza wrażliwości; Łańcuch dostaw

• Czasopismo: Management and Production Engineering Review
• Rocznik: 2014
• Tom: 5
• Numer: nr 3
• Strony: 45--52

Twórcy

autor

Hoda Mahmoudi

• Mazandaran University of Science and Technology, Iran

autor

Hamed Fazlollahtabar

• Iran University of Science and Technology

Bibliografia

• [1] Rogers D.S., Tibben-Lembke R.S., Going backward: reverse logistics trends and practices, Nevada, Reno: Reverse Logistics Executive Council, 1999.
• [2] Kannan G., Fuzzy approach for the selection of third party reverse logistics provider, Asia Pacific Journal of Marketing and Logistics, 21 (3), 397-416, 2009.
• [3] Lee J., Gen E., Rhee M.K.G., Network model and optimization of reverse logistics by hybrid genetic algorithm, Computers and Industrial Engineering, 56 (3), 951-64, 2009.
• [4] Stock J.K., Reverse logistics, white paper, council of logistics management, IL: Oak Brook, 1992.
• [5] Liu X., Tanaka M., Matsui Y., Electrical and electronic waste management in China: Progress and the barrier to overcome, Waste Management and Research, 24, 92-101, 2006.
• [6] He W., Li G., Ma X., Wang H., Huang J., Xu M. et al., WEEE recovery strategies and the WEEE treatment status in China, Journal of Hazardous Materials, 136 (3), 502-512, 2006.
• [7] Kim K.B., Song I.S., Jeong B.J., Supply planning model for remanufacturing system in reverse logistics environment, Computers & Industrial Engineering, 51 (2), 279-287, 2006.
• [8] Aras N., Aksen D., Tanugur A.G., Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles, European Journal of Operational Research, 191, 1223-40, 2008.
• [9] Teunter R., Kaparis K., Tang O., Multi-product economic lot scheduling problem with separate production lines for manufacturing and remanufacturing, European Journal of Operational Research, 191, 1241-1253, 2008.
• [10] Zuidwijk R., Krikke H., Strategic response to EEE returns: product ecodesign or new recovery processes?, European Journal of Operational Research, 191, 1206-1222, 2008.
• [11] Du F., Evans G.W., A bi-objective reverse logistics network analysis for post-sale service, Computers &Operations Research, 35, 2617-34, 2008.
• [12] Kannan G., Sasikumar P., Devika K., A genetic algorithm approach for solving a closed loop supply chain model: a case of battery recycling, Appl.Math. Model., 34 (3), 655-670, 2010.
• [13] Amin S.H., Zhang G., A proposed mathematical model for closed-loop network configuration based on product life cycle, Int. J. Adv. Manuf. Technol., 58 (5), 791-801, 2012.
• [14] Du F., Evans G.W., A bi-objective reverse logistics network analysis for post-sale service, Comput. Oper. Res., 35 (8), 2617-2634, 2008.
• [15] Jayaraman V., Patterson R.A., Rolland E., The design of reverse distribution networks: models and solution procedures, European Journal of Operational Research, 150, 128-149, 2003.
• [16] Ko H.J., Evans G.W., A genetic-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs, Computers & Operations Research, 34, 346-66, 2007.
• [17] Pati R.K., Vrat P., Kumar P., A goal programming model for paper recycling system, The International Journal of Management Science, Omega, 36 (3), 405-417, 2008.
• [18] Salema M.I.G., Barbosa-Povoa A.P., Novais A.Q., An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty, European Journal of Operational Research, 179, 1063-1077, 2007.
• [19] Sheu J.B., Chou Y.H., Hu C.C., An integrated logistics operational model for green-supply chain management, Transport. Res. Part E: Logist. Transport. Rev., 41 (4), 287-313, 2005.
• [20] Fleischmann M., Beullens P., Bloemhof-Ruwaard J.M., Van Wassenhove L.N., The impact of product recovery on logistics network design, Prod. Oper. Manag., 10 (2), 156-173, 2001.
• [21] Kannan G., Noorul Haq A., Devika M., Analysis of closed loop supply chain using genetic algorithm and particle swarm optimization, Int. J. Prod. Res., 47 (5), 1175-1200, 2009.
• [22] Shi J., Zhang G., Sha J., Amin S.H., Coordinating production and recycling decision with stochastic demand and return, J. Syst. Sci. Syst. Eng., 19 (4), 385-407, 2010.
• [23] Schultmann F., Engels B., Rentz O., Closed-loop supply chains for spent batteries, Interfaces, 33, 57-71, 2003.
• [24] Listes O., A generic stochastic model for supply-andreturn network design, Comput. Oper. Res., 34 (??), 417-442, 2007.
• [25] Wang H., Hsu H., Resolution of an uncertain closedloop logistics model: an application to fuzzy linear programs with risk analysis, J. Environ. Manage., 91 (11), 2148-2162, 2010.
• [26] Gupta A., Evans G.W., A goal programming model for the operation of closed-loop supply chains, Eng. Optim., 41 (8), 713-735, 2009.
• [27] Pishvaee M.S., Farahani R.Z., Dullaert W., A memetic algorithm for bi-objective integrated forward/reverse logistics network design, Comput. Oper. Res., 37 (6), 1100-1112, 2010.
• [28] Min H., Ko C.S., Ko H.J., The spatial and temporal consolidation of returned products in a closed-loop supply chain network, Comput. Ind. Eng., 51 (2), 309-320, 2006.
• [29] Fuente M.V.D., Ros L., Cardos M., Integrating forward and reverse supply chains: application to a metal-mechanic company, Int. J. Prod. Econ., 111 (2), 782-792, 2008.
• [30] Lee D., Dong M., A heuristic approach to logistics network design for end-of-lease computer products recovery, Transportation Research Part E, 44, 455-474, 2008.

Identyfikatory

DOI

10.2478/mper-2014-0026