Swarm Intelligence in Solving Stochastic Capacitated Vehicle Routing Problem

被引:1
作者
Mandziuk, Jacek [1 ,2 ]
Swiechowski, Maciej [3 ]
机构
[1] Warsaw Univ Technol, Fac Math & Informat Sci, Warsaw, Poland
[2] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
[3] Polish Acad Sci, Syst Res Inst, Warsaw, Poland
来源
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2017, PT II | 2017年 / 10246卷
关键词
Vehicle routing problem; Traffic jams; Particle swarm optimization; Ant colony optimization; Imperfect information;
D O I
10.1007/978-3-319-59060-8_49
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the two most popular Swarm Intelligence approaches (Particle Swarm Optimization and Ant Colony Optimization) are compared in the task of solving the Capacitated Vehicle Routing Problem with Traffic Jams (CVRPwTJ). The CVRPwTJ is a highly challenging optimization problem for the following reasons: while the CVRP is already a problem of NP complexity, adding another stochastic layer to its definition (related to stochastic occurrence of traffic jams while traversing the planned vehicle routes) further increases the problem's difficulty by requiring that potential solution methods be capable of on-line adaptation of the routes, in response to changing traffic conditions. The results presented in the paper shed light on the underlying differences between ACO and PSO in terms of their suitability to solving particular instances of CVRPwTJ.
引用
收藏
页码:543 / 552
页数:10
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