Abstract
One of the most important and yet complex decision-making problems in the area of transportation programming issues is vehicle routing problem. There are various exact, heuristic, and metaheuristic methods presented for solving different vehicle routing problems. In this manuscript, a mathematical model and a new heuristic solution method are proposed for solving multi-depot vehicle routing problem with time windows and different types of vehicles. In this problem, depots must serve customers between their fuzzy time windows with vehicles having different capacities, velocities, and costs. For this purpose, the mathematical model for multi-depot routing problem is developed to consider the mentioned circumstances. The objectives of this model is travel distance reduction and customers’ service level increscent which leads to cost and service time reduction. For complexity of this problem and much computational time of exact solutions of developed model, a heuristic approach is proposed. This systematic approach has some steps as: customer clustering, routing, vehicle type determination, scheduling, and routes improvement using simulated annealing and customer service level improvement. The efficiency of the proposed method is analyzed by a case study in ISACO Co. Results show that the method is efficient and applicable in industries.
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Balakrishnan N (1993) Simple heuristic for vehicle routing problem with soft time windows. Oper Res Soc 44:279–287
Balseiro SR, Loiseau I, Ramonet J (2011) An Ant Colony algorithm hybridized with insertion heuristics for the Time Dependent Vehicle Routing Problem with Time Windows. Comput Oper Res 38:954–966
Calvete HI, Gale C, Oliveros M, Sanchez-Valverde B (2007) A goal programming approach to vehicle routing problem with soft time windows. Eur J Oper Res 44:1720–1733
Chiang WC, Russell RA (2004) A metaheuristic for vehicle routing problem with soft time windows. Oper Res Soc 55:1298–1310
Chiang WC, Russell RA (2004) Integrating purchasing and routing in a propane gas supply chain. Eur J Oper Res 154:710–729
Dondo R, Cerda J (2007) A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows. Eur J Oper Res 176:1478–1507
Farhang Moghadam B, Ruiz R, Sadjadi SR (2012) Vehicle routing problem with uncertain demands: an advanced particle swarm algorithm. Comput Ind Eng 62:306–317
Ferland JA, Fortin L (1989) vehicle routing with sliding time windows. Eur J Oper Res 38:213–226
Gillet BE, Miller LR (1974) A heuristic algorithm for vehicle dispatching problem. J Oper Res 22:340–349
Giosa ID, Tansini IL, Viera IC (2002) New assignment algorithm for multi-depot vehicle routing problem. J Oper Res Soc 53:977–984
Goksal FP, Karaoglan I, Altiparmak F (2013) A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Comput Ind Eng 66:39–53
Ho W, George TS, Ping J, Henry CW (2008) A hybrid genetic algorithm for the multi-depot vehicle routing problem. Eng Appl Artif Intell 21:548–557
Hong L (2012) An improved LNS algorithm for real time vehicle routing problem with time windows. Comput Oper Res 39:151–163
Mirabi M, Fatemi Ghomi SMT, Jolai F (2010) Efficient stochastic hybrid heuristics for the multi-depot vehicle routing problem. Robot Comput Integr Manuf 26:564–569
Salhi S, Sari M (1997) A multi-level composite search heuristic for the multi depot vehicle fleet mix problem. Eur J Oper Res 103:95–112
Savelsbergh M (1985) Local search for routing problems with time windows. Ann Oper Res 4:285–305
Sexton T, Choi Y (1986) Pick-up and delivery of partial loads with soft time windows. Am J Math Manag Sci 6:396–398
Solomon MM (1987) Algorithms for the vehicle routing scheduling problem with time window constraints. Oper Res 35:245–265
Solomon MM, Desrosiers J (1988) Time windows constrained routing and scheduling problems. Transp Sci 22:1–13
Sur B, Heany H, Gyu C, Meny G (2007) Integrated GA-VRP solver for multi depot system. Comput Ind Eng 53:233–240
Tan KC, Cheong CY, Goh CK (2007) Solving multi objective vehicle routing problem with stochastic demand via-evolutionary computation. Eur J Oper Res 177:813–839
Tang J, Pan Z, Richard YK, Lau H (2009) Vehicle routing problem with fuzzy time windows. Fuzzy Set Syst 160:683–695
Tillman FA, Cain TM (1972) An upper bound algorithm for the single and multiple-terminal delivery problem. Manag Sci 18:662–682
Wang HF, Chen YY (2012) A genetic algorithm for the simultaneous delivery and pickup problems with time window. Comput Ind Eng 62:84–95
Wang HF, Wen YP (2002) Time-constrained Chinese postman problems. Comput Mathe Appl 44:375–387
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zheng Y, Liu B (2006) Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm. Appl Math Comput 176:673–683
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Adelzadeh, M., Mahdavi Asl, V. & Koosha, M. A mathematical model and a solving procedure for multi-depot vehicle routing problem with fuzzy time window and heterogeneous vehicle. Int J Adv Manuf Technol 75, 793–802 (2014). https://doi.org/10.1007/s00170-014-6141-8
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DOI: https://doi.org/10.1007/s00170-014-6141-8