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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Particle Swarm Optimization Combined with Tabu Search in a Multi-agent Model for Flexible Job Shop Problem
verfasst von : Abir Henchiri, Meriem Ennigrou
Erschienen in: Advances in Swarm Intelligence
Verlag: Springer Berlin Heidelberg
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Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine and has a processing time depending on the machine used. The objective is to minimize the makespan, i.e., the total duration of the schedule. In this article, we propose a multi-agent model based on the hybridization of the tabu search (TS) method and particle swarm optimization (PSO) in order to solve FJSP. Different techniques of diversification have also been explored in order to improve the performance of our model. Our approach has been tested on a set of benchmarks existing in the literature. The results obtained show that the hybridization of TS and PSO led to promising results.