A hybrid multiobjective evolutionary algorithm for solving truck and trailer vehicle routing problems

被引：0

作者：

Tan, KC ^{[1
]}

Lee, TH ^{[1
]}

Chew, YH ^{[1
]}

Lee, LH ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore

来源：

CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper considers a transportation problem for moving empty or laden containers for a logistic company. A model for this truck and trailer vehicle routing problem (TTVRP) is first constructed in the paper. The solution to the TTVRP consists of finding a complete routing schedule for serving the jobs with minimum routing distance and number of trucks, subject to a number of constraints such as time windows and availability of trailers. To solve such a multiobjective and multi-modal combinatorial optimization problem, a hybrid multiobjective evolutionary algorithm (HMOEA) is applied to find the Pareto optimal routing solutions for the TTVRP. Detailed analysis is performed to extract useful decision-making information from the multiobjective optimization results The computational results have shown that the HMOEA is effective for solving multiobjective combinatorial problems, such as finding useful trade-off solutions for the TTVRP.

引用

页码：2134 / 2141

页数：8

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