A genetic algorithm approach for location-inventory-routing problem with perishable products

Journal of Manufacturing Systems

Volumn 42, Issue , 2017, Pages 93-103

  Hiassat, Abdelhalim ^a   Diabat, Ali ^b   Rahwan, Iyad ^c  

^a UNIVERSITY OF WATERLOO   (Canada)

^b KHALIFA UNIVERSITY   (United Arab Emirates)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Facility location; Genetic algorithms; Integer programming; Inventory management; Perishable products; Supply chain; Vehicle routing

Indexed keywords

GENETIC ALGORITHMS; HEURISTIC ALGORITHMS; INTEGER PROGRAMMING; INVENTORY CONTROL; LOCATION; POLYNOMIAL APPROXIMATION; POLYNOMIALS; ROUTING ALGORITHMS; SUPPLY CHAINS; VEHICLE ROUTING;

FACILITY LOCATIONS; GENETIC ALGORITHM APPROACH; INVENTORY MANAGEMENT; INVENTORY ROUTING PROBLEMS; LOCAL SEARCH HEURISTICS; LOCATION DECISIONS; NEAR-OPTIMAL SOLUTIONS; PERISHABLE PRODUCT;

PROBLEM SOLVING;

EID: 85002862279     PISSN: 02786125     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmsy.2016.10.004     Document Type: Article

References (45)

1. [1] Miller, T., Hierarchical operations and supply chain planning. 2002, Springer, New, York NY.
2. [2] Stevens, G.C., Integrating the supply chain. Int J Phys Distrib Logist Manage 19:8 (1989), 3–8.
3. [3] Gunasekaran, A., Patel, C., Tirtiroglu, E., Performance measures and metrics in a supply chain environment. Int J Oper Prod Manage 21:1/2 (2001), 71–87.
4. [4] Cavinato, J.L., A total cost/value model for supply chain competitiveness. J Bus Logist, 13, 1992 p. 285.
5. [5] Chopra, S., Meindl, P., Supply chain management: strategy, planning, and operation. 2007, Pearson Prentice Hall.
6. [6] Silver, E., Pyke, D.F., Peterson, R., Inventory management and production planning and scheduling. 1998.
7. [7] Diabat, A., Richard, J.-P., Codrington, C., A lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design. Ann Oper Res 203:1 (2013), 55–80.
8. [8] Nagy, G., Salhi, S., Location-routing: issues, models and methods. Eur J Oper Res 177:2 (2007), 649–672.
9. [9] Wu, T.-H., Low, C., Bai, J.-W., Heuristic solutions to multi-depot location-routing problems. Comput Oper Res 29:10 (2002), 1393–1415.
10. [10] Baita, F., Ukovich, W., Pesenti, R., Favaretto, D., Dynamic routing-and-inventory problems: a review. Transp Res Part A: Policy Pract 32:8 (1998), 585–598.
11. [11] Moin, N.H., Salhi, S., Inventory routing problems: a logistical overview. J Oper Res Soc 58:9 (2007), 1185–1194.
12. [12] Daskin, M., Coullard, C., Shen, Z.-J., An inventory-location model: formulation, solution algorithm and computational results. Ann Oper Res 110:1–4 (2002), 83–106.
13. [13] Shen, Z.-J.M., Coullard, C., Daskin, M.S., A joint location-Inventory model. Transp Sci 37:1 (2003), 40–55.
14. [14] Le, T., Diabat, A., Richard, J.-P., Yih, Y., A column generation-based heuristic algorithm for an inventory routing problem with perishable goods. Optim Lett 7:7 (2013), 1481–1502.
15. [15] Bertsimas, D.J., Simchi-Levi, D., A new generation of vehicle routing research: robust algorithms, addressing uncertainty. Oper Res 44:2 (1996), 286–304.
16. [16] Max Shen, Z.J., Qi, L., Incorporating inventory and routing costs in strategic location models. Eur J Oper Res 179:2 (2007), 372–389.
17. [17] Diabat, A., Battaïa, O., Nazzal, D., An improved Lagrangian relaxation-based heuristic for a joint location-inventory problem. Comput Oper Res 61 (2015), 170–178.
18. [18] Diabat, A., Richard, J.-P., An integrated supply chain problem: a nested lagrangian relaxation approach. Ann Oper Res 229:1 (2015), 303–323.
19. [19] Javid, A.A., Azad, N., Incorporating location, routing and inventory decisions in supply chain network design. Transp Res Part E: Logist Transp Rev 46:5 (2010), 582–597.
20. [20] Diabat, A., A capacitated facility location and inventory management problem with single sourcing. Optim Lett, 2015, 1–16.
21. [21] Diabat, A., Theodorou, E., A location-inventory supply chain problem: reformulation and piecewise linearization. Comput Ind Eng 90 (2015), 381–389.
22. [22] Liu, S.C., Lee, S.B., A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration. Int J Adv Manuf Technol 22:11-12 (2003), 941–950.
23. [23] Ambrosino, D., Grazia Scutellà, M., Distribution network design: new problems and related models. Eur J Oper Res 165:3 (2005), 610–624.
24. [24] Giri, B.C., Chaudhuri, K.S., Deterministic models of perishable inventory with stock-dependent demand rate and nonlinear holding cost. Eur J Oper Res 105:3 (1998), 467–474.
25. [25] Padmanabhan, G., Vrat, P., EOQ models for perishable items under stock dependent selling rate. Eur J Oper Res 86:2 (1995), 281–292.
26. [26] Dye, C.-Y., Ouyang, L.-Y., An EOQ model for perishable items under stock-dependent selling rate and time-dependent partial backlogging. Eur J Oper Res 163:3 (2005), 776–783.
27. [27] Hsu, C.-I., Hung, S.-F., Li, H.-C., Vehicle routing problem with time-windows for perishable food delivery. J Food Eng 80:2 (2007), 465–475.
28. [28] Koskosidis, Y.A., Powell, W.B., Solomon, M.M., An optimization-based heuristic for vehicle routing and scheduling with soft time window constraints. Transp Sci 26:2 (1992), 69–85.
29. [29] Sexton, T.R., Choi, Y.-M., Pickup and delivery of partial loads with soft time windows. Am J Math Manage Sci 6:3–4 (1986), 369–398.
30. [30] Diabat, A., Al-Salem, M., A joint location inventory problem with environmental considerations. Int J Prod Econ, 2014 in press.
31. [31] Dimopoulos, C., Zalzala, A.M.S., Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons. Evol Comput IEEE Trans 4:2 (2000), 93–113.
32. [32] Diabat, A., Aouam, T., Ozsen, L., An evolutionary programming approach for solving the capacitated facility location problem with risk pooling. Int J Appl Decis Sci 2:4 (2009), 389–405.
33. [33] Diabat, A., Deskoores, R.M., A hybrid genetic algorithm based heuristic for an integrated supply chain problem. J Manuf Syst 38 (2015), 172–180.
34. [34] Diabat, A., Al-Salem, M., An integrated supply chain problem with environmental considerations. Int J Prod Econ 164 (2015), 330–338.
35. [35] Diabat, A., Hybrid algorithm for a vendor managed inventory system in a two-echelon supply chain. Eur J Oper Res 238:1 (2014), 114–121.
36. [36] Alp, O., Erkut, E., Drezner, Z., An efficient genetic algorithm for the p-median problem. Ann Oper Res 122:1–4 (2003), 21–42.
37. [37] Baker, B.M., Ayechew, M.A., A genetic algorithm for the vehicle routing problem. Comput Oper Res 30:5 (2003), 787–800.
38. [38] Skok, M., Skrlec, D., Krajcar, S., The genetic algorithm method for multiple depot capacitated vehicle routing problem solving. In Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings. Fourth International Conference on, 2000, 520–526.
39. [39] Zhou, G., Min, H., Gen, M., The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach. Comput Ind Eng 43:1 (2002), 251–261.
40. [40] Min, H., Jeung Ko, H., Seong Ko, C., A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns. Omega 34:1 (2006), 56–69.
41. [41] Lau, H.C.W., Chan, T., Tsui, W.T., Pang, W.K., Application of genetic algorithms to solve the multidepot vehicle routing problem. Autom Sci Eng, IEEE Trans 7:2 (2010), 383–392.
42. [42] Alshamsi, A., Diabat, A., A reverse logistics network design. J Manuf Syst 37:3 (2015), 589–598.
43. [43] Santibanez-Gonzalez, E.D.R., Diabat, A., Solving a reverse supply chain design problem by improved Benders decomposition schemes. Comput Ind Eng 66:4 (2013), 889–898.
44. [44] Al-Salem, M., Diabat, A., Dalalah, D., Alrefaei, M., A closed-loop supply chain management problem: reformulation and piecewise linearization. J Manuf Syst, 2016.
45. [45] Hiassat, A., Diabat, A., A location-inventory-routing problem with perishable products. Proceedings of the 41st International Conference on Computers and Industrial Engineering, 2011.