Improved simulated annealing algorithm for capacitated vehicle routing problem

被引:0
|
作者
Shang Z. [1 ]
Gu J. [2 ]
Wang J. [1 ]
机构
[1] School of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu
[2] Mechanical Information Research Center, Jiangsu University, Zhenjiang
关键词
Multi-constraint coupling solution; Neighborhood search; Simulated annealing algorithm; Vehicle routing problem;
D O I
10.13196/j.cims.2021.08.009
中图分类号
学科分类号
摘要
To solve the Capacitated Vehicle Routing Problem (CVRP), an improved simulated annealing algorithm with the tempering operation was presented. Based on the characteristic analysis of route optimization under multiple constraints, the solution framework of simulated annealing operation with simple structure and independent functional modules was constructed, which could facilitate the coupling of relevant constraints and algorithms. Under the arithmetic framework, the acceptance rules for the better solution were altered, and the balance between global searching and local searching was achieved through the tempering operation. A compulsory random neighborhood transformation strategy was designed to improve the quality of new solution generation under multiple constraints. The entire algorithm was constructed by combining the initial solution method. Simulation results on classic benchmarks with different types demonstrated the effectiveness of the presented algorithm. This study of the corresponding solution framework and optimization method could provide a reference for the relevant multi-constraint coupling solution. © 2021, Editorial Department of CIMS. All right reserved.
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页码:2260 / 2269
页数:9
相关论文
共 20 条
  • [11] TAO Yi, WANG Fan, An effective tabu search approach with improved loading algorithms for the 3L-CVRP, Computers & Operations Research, 55, pp. 127-140, (2015)
  • [12] ZHANG Zhenzhen, WEI Lijun, LIM A., An evolutionary local search for the capacitated vehicle routing problem minimizing fuel consumption under three-dimensional loading constraints, Transportation Research Part B, 82, pp. 20-35, (2015)
  • [13] LEUNG S C H, ZHANG Z, ZHANG D, Et al., A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints, European Journal of Operational Research, 225, 2, pp. 199-210, (2013)
  • [14] REIL S, BORTFELDT A, MONCH L., Heuristics for vehicle routing problems with backhauls, time windows, and 3D loading constraints, European Journal of Operational Research, 266, 3, pp. 877-894, (2018)
  • [15] DOMINGUEZ O, JUAN A A, BARRIOS B, Et al., Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet, Annals of Operations Research, 236, 2, pp. 383-404, (2016)
  • [16] YANG Xiang, FAN Houming, XU Zhenlin, Et al., Optimization of open multi-depot vehicle routing problem with fuzzy demand, Computer Integrated Manufacturing Systems, 25, 2, pp. 207-217, (2019)
  • [17] Vehicle routing data sets
  • [18] GENDREAU M, IORI M, LAPORTE G, Et al., A Tabu search heuristic for the vehicle routing problem with two-dimensional loading constraints, Networks, 51, 1, pp. 4-18, (2008)
  • [19] LANG Maoxiang, Optimal dispatching model and algorithm for distribution vehicles, (2009)
  • [20] WRIGHT G C W., Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, 4, pp. 568-581, (1964)