Efficient stochastic hybrid heuristics for the multi-depot vehicle routing problem

被引：71

作者：

Mirabi, M. ^{[2
]}

Ghomi, S. M. T. Fatemi ^{[1
]}

Jolai, F. ^{[3
]}

机构：

[1] Amir Kabir Univ Technol, Dept Ind Engn, Tehran, Iran

[2] Yazd Univ, Dept Ind Engn, Fac Engn, Yazd, Iran

[3] Univ Tehran, Dept Ind Engn, Coll Engn, Tehran, Iran

来源：

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING | 2010年 / 26卷 / 06期

关键词：

Multi-depot vehicle routing problem; Hybrid heuristic; Simulated annealing; ALGORITHMS;

D O I：

10.1016/j.rcim.2010.06.023

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The paper addresses the problem of multi-depot vehicle routing in order to minimize the delivery time of vehicle objective. Three hybrid heuristics are presented to solve the multi-depot vehicle routing problem. Each hybrid heuristic combines elements from both constructive heuristic search and improvement techniques. The improvement techniques are deterministic, stochastic and simulated annealing (SA) methods. Experiments are run on a number of randomly generated test problems of varying depots and customer sizes. Our heuristics are shown to outperform one of the best-known existing heuristic. Statistical tests of significance are performed to substantiate the claims of improvement. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：564 / 569

页数：6

共 22 条

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Aarts E., 1989, Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing

[2]

Chao IM, 1993, AM J MATH MGMT SCI, V13, P371

[3] SCHEDULING OF VEHICLES FROM CENTRAL DEPOT TO NUMBER OF DELIVERY POINTS [J].