A Memetic Algorithm for the Tool Switching Problem

被引：0

作者：

Amaya, Jhon Edgar ^{[1
]}

Cotta, Carlos ^{[2
]}

Fernandez, Antonio J. ^{[2
]}

机构：

[1] UNET, LCAR, San Cristobal, Venezuela

[2] Univ Malaga, ETSI Informat, Dept Lenguajes Ciencias Computac, E-29071 Malaga, Spain

来源：

HYBRID METAHEURISTICS, PROCEEDINGS | 2008年 / 5296卷

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 deals with the Tool Switching Problem (ToSP), a well-known problem in operations research. The ToSP involves determining a job sequence and the tools to be loaded on a machine with the goal of minimizing the total number of tool switches. This problem has been tackled by a number of algorithmic approaches in recent years. Here, we propose a memetic algorithm that combines a problem-specific permutational genetic algorithm with a hill-climbing procedure. It is shown that this combined approach outperforms each of the individual algorithms, as well as an ad-hoc beam search heuristic defined in the literature for this problem.

引用

页码：190 / +

页数：3

共 22 条

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