A Memetic Algorithm for the Tool Switching Problem

Authors:
Jhon Edgar Amaya;Carlos Cotta;Antonio J. Fernández
Affiliations:
Laboratorio de Computación de Alto Rendimiento (LCAR), Universidad Nacional Experimental del Táchira (UNET), San Cristóbal, Venezuela;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain 29071;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain 29071
Venue:
HM '08 Proceedings of the 5th International Workshop on Hybrid Metaheuristics
Year:
2008

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Abstract

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.