A parallel hybrid heuristic for the multicommodity capacitated location problem with balancing requirements

被引：9
|
作者：
Gendron, B
Potvin, JY
Soriano, P
机构：
[1] Univ Montreal, Ctr Rech Transports, Montreal, PQ H3C 3J7, Canada
[2] Univ Montreal, Dept Informat & Rech Operat, Montreal, PQ H3C 3J7, Canada
[3] Ecole Hautes Etud Commerciales, Montreal, PQ H3T 2A7, Canada
来源：
PARALLEL COMPUTING | 2003年 / 29卷 / 05期
关键词：
multicommodity capacitated location problem; slope scaling; variable neighborhood descent; hybrid; adaptive memory;
D O I：
10.1016/S0167-8191(03)00044-9
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, a parallel hybrid heuristic is developed for the multicommodity capacitated location problem with balancing requirements. The hybrid involves variable neighborhood descent (VND) and slope scaling (SS). Both methods evolve in parallel within a master-slave architecture where the slave processes communicate through adaptive memories. Numerical results are reported on different types of randomly generated instances, using an increasing number of processors and different distributions of processes between SS and VND. (C) 2003 Elsevier Science B.V. All rights reserved.
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页码：591 / 606
页数：16
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