A hybrid genetic algorithm for a dynamic logistics network with multi-commodities and components
RAIRO - Operations Research - Recherche Opérationnelle, Tome 45 (2011) no. 2, pp. 153-178.

Various topics related to reverse logistics have been discussed over the years. Most of them have assumed that facilities are kept open once they are established, and no returned products or recovery parts are stocked in intermediate recycling stations. However, firms may have the right to repeatedly open or close their facilities according to their economic benefits if they can acquire their facilities by lease. It also turns out that intermediate recycling stations like collection centers and disassembly centers usually stock returned products or parts in their facilities. By simultaneously relaxing these two assumptions, this study explores a logistics system with multiple items, each of which consists of some components among a variety of spare parts. The purpose is to maximize the total logistics costs by establishing a production schedule and reverse logistics framework over finite time periods for a logistics system. The mathematical model established in this study is a constrained linear integer programming problem. A genetic based algorithm is developed with the help of linear programming to find solutions to this problem. Limited computational experiments show that the proposed approach can produce better feasible solutions than the well-known CPLEX 10.0 software.

DOI : https://doi.org/10.1051/ro/2011105
Classification : 90-XX,  90-08
Mots clés : reverse logistics, genetic algorithm, constrained integer programming, production schedule, inventory
@article{RO_2011__45_2_153_0,
     author = {You, Peng-Sheng and Hsieh, Yi-Chih and Chen, Hisn-Hung},
     title = {A hybrid genetic algorithm for a dynamic logistics network with multi-commodities and components},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {153--178},
     publisher = {EDP-Sciences},
     volume = {45},
     number = {2},
     year = {2011},
     doi = {10.1051/ro/2011105},
     zbl = {1261.90005},
     mrnumber = {2855950},
     language = {en},
     url = {http://www.numdam.org/item/RO_2011__45_2_153_0/}
}
You, Peng-Sheng; Hsieh, Yi-Chih; Chen, Hisn-Hung. A hybrid genetic algorithm for a dynamic logistics network with multi-commodities and components. RAIRO - Operations Research - Recherche Opérationnelle, Tome 45 (2011) no. 2, pp. 153-178. doi : 10.1051/ro/2011105. http://www.numdam.org/item/RO_2011__45_2_153_0/

[1] N. Brahimi, S. Dauzere-Peres, N.M. Najid and A. Nordli, Single item lot sizing problems. Eur. J. Oper. Res. 168 (2006) 1-16. | MR 2162179 | Zbl 1077.90001

[2] C. Canel, B.M. Khumawala, J. Law and A. Loh, An algorithm for the capacitated, multi-commodity multi-period location problem. Comput. Oper. Res. 28 (2001) 411-427. | MR 1810450 | Zbl 1080.90535

[3] K.W. Chau, A two-stage dynamic model on allocation of construction facilities with genetic algorithm. Automat. Constr. 13 (2004) 481-490.

[4] J. Dias, M.E. Captivo and J. Climaco, Efficient primal-dual heuristic for a dynamic location problem. Comput. Oper. Res. 34 (2007) 1800-1823. | MR 2259194 | Zbl 1159.90439

[5] S.D. Ekşioğlu, Optimizing integrated production, inventory and distibution problems in supply chains. Ph. D. thesis, University of Florida, USA (2002) (fcla.edu/fcla/etd/UFE0000529).

[6] M. Fleischmann, P. Beullens and J.M. Bloemhof-Ruwaard, The impact of product recovery on logistics network design. Prod. Oper. Manage. 10 (2001) 156-173.

[7] Y. Hinojosa, J. Kalcsics, S. Nickel, J. Puerto and S. Velten, Dynamic supply chain design with inventory. Comput. Oper. Res. 35 (2008) 373-391. | MR 2318874 | Zbl 1141.90021

[8] R. Jans and Z. Degraeve, Meta-heuristics for dynamic lot sizing: A review and comparison of solution approaches. Eur. J. Oper. Res. 177 (2007) 1855-1875. | MR 2360955 | Zbl 1102.90002

[9] V. Jayaraman, R.A. Patterson and E. Rolland, The design of reverse distribution network: Model and solution procedures. Eur. J. Oper. Res. 150 (2003) 128-149. | MR 1989696 | Zbl 1023.90501

[10] J. Krarup and P.M. Pruzan, The simple plant location problem: survey and synthesis. Eur. J. Oper. Res. 12 (1983) 36-81. | MR 691416 | Zbl 0506.90018

[11] H.J. Ko and G.W. Evans, A genetic algorithm-based heuristic for dynamic integrated forward/reverse logistics network for 3PLs. Comput. Oper. Res. 34 (2007) 346-366. | Zbl 1113.90028

[12] H.J. Ko, C.S. Ko and T. Kim, A hybrid optimization/simulation approach for a distribution network design of 3PLS. Comput. Ind. Eng. 50 (2006) 440-449.

[13] J. Krarup and P.M. Pruzan, The simple plant location problem: Survey and synthesis. Eur. J. Oper. Res. 12 (1983) 36-57. | MR 691416 | Zbl 0506.90018

[14] R.D. Kusumastuti, R. Piplani and G.H. Lim, Redesigning closed-loop service network at a computer manufacturer: A case study. Int. J. Prod. Econ. 111 (2008) 244-260.

[15] I.M. Langella, Heuristics for demand-driven disassembly planning. Comput. Oper. Res. 34 (2007) 552-577. | Zbl 1109.90012

[16] H. Lee and M. Dong, A heuristic approach to logistics network design for end-of-lease computer products recovery. Transport. Res. E. 44 (2008) 455-474.

[17] K. Lieckens and N. Vandaele, Reverse logistics network design with stochastic lead times. Comput. Oper. Res. 34 (2007) 395-416. | Zbl 1113.90023

[18] Z. Lu and N. Bostel, A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Comput. Oper. Res. 34 (2007) 299-323. | MR 2246736 | Zbl 1113.90025

[19] E. Melachrinoudis, H. Min and X. Wu, A multiobjective model for the dynamic location of landfills. Location Science 3 (1995) 143-166. | Zbl 0916.90181

[20] M.T. Melo, S. Nickel and F.S. Gama, Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning. Comput. Oper. Res. 33 (2005) 181-208. | Zbl 1077.90006

[21] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. 3rd edition, Springer-Verlag, London, UK (1996). | MR 1240748 | Zbl 0841.68047

[22] H. Min and H.J. Ko, The dynamic design of a reverse logistics network from the perspective of third-party logistics service providers. Int. J. Prod. Econ. 113 (2008) 176-192.

[23] H. Min, C.S. Ko and H.J. Ko, The spatial and temporal consolidation of returned products in a closed-loop supply chain network. Comput. Ind. Eng. 51 (2006) 309-320.

[24] G.C. Onwubolu and B.V. Babu, New optimization techniques in engineering. Springer-Verlag, Berlin, Heidelberg (2004) Chap. 2. | Zbl 1051.90002

[25] M.S. Pishvaee, R.Z. Farahani and W. Dullaert, A memetical gorithm for bi-objective integrated forward/reverse logistics network design. Comput. Oper. Res. 37 (2005) 181-208. | Zbl 1178.90060

[26] C. Prahinski and C. Kocabasoglu, Empirical research opportunities in reverse supply chains. Omega-Int. J. Manage. Sci. 34 (2006) 519-532.

[27] M.I.G. Salema, A.P. Barbosa-Povoa and A.Q. Novais, An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. Eur. J. Oper. Res. 179 (2007) 1063-1077. | Zbl 1163.90371

[28] E.A. Silver, D.F. Pyke and R. Peterson, Inventory management and production planning and scheduling. 3rd edition, John Wiley & Sons, USA (1998).

[29] M. Sodhi and B. Reimer, Models for recycling end-of-life products. OR-Spectrum 23 (2001) 97-115. | Zbl 1015.90006

[30] T. Spengler, H. Püchert, T. Penkuhn and O. Rentz, Environmental integrated production and recycling management. Eur. J. Oper. Res. 97 (1997) 308-326. | Zbl 0930.90033

[31] Z. Yongsheng and W. Shouyang, Generic Model of Reverse Logistics Network Design. J. Transport. Syst. Eng. Inf. Tech. 8 (2008) 71-78.

[32] http://www.lindo.com/index.php