An Ant Colony Optimization Method for the Capacitated Vehicle Routing Problem with Stochastic Demands

被引：0
|
作者：
Janjarassuk, Udom [1 ]
Masuchun, Ruedee [1 ]
机构：
[1] King Mongkuts Inst Technol Ladkrabang, Fac Engn, Bangkok, Thailand
来源：
2016 20TH INTERNATIONAL COMPUTER SCIENCE AND ENGINEERING CONFERENCE (ICSEC) | 2016年
关键词：
Ant colony optimization; Vehicle routing problem; Stochastic demands; Simulation; ALGORITHM; BRANCH;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The ant colony optimization (ACO) method has been extensively studied recently for solving many combinatorial optimization problems. In this paper, an ant colony optimization method for solving the vehicle routing problem with stochastic demands is presented. The 2-opt local search is employed within the ACO algorithm to improve the qualities of the solutions. Simulation technique is used for the estimate of the expected cost under stochastic demands. Computational results are also reported.
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页数：5
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