A Memetic Algorithm for the Multidimensional Assignment Problem

被引：0
|
作者：
Gutin, Gregory [1 ]
Karapetyan, Daniel [1 ]
机构：
[1] Univ London, London, England
来源：
ENGINEERING STOCHASTIC LOCAL SEARCH ALGORITHMS: DESIGNING, IMPLEMENTING AND ANALYZING EFFECTIVE HEURISTICS | 2009年 / 5752卷
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D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The Multidimensional Assignment Problem (MAP or s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s have also a number of applications. In this paper we propose a memetic algorithm for MAP that is a combination of a genetic algorithm with a local search procedure. The main contribution of the paper is ail idea of dynamically adjusted generation size, that yields ail outstanding flexibility of the algorithm to perform well for both small and large fixed running times.
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页码：125 / 129
页数：5
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