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Erschienen in:
2015 | OriginalPaper | Buchkapitel
MATS–JSTL: A Multi-Agent Model Based on Tabu Search for Job Shop Problem with Time Lags
verfasst von : Madiha Harrabi, Belkahla Driss Olfa
Erschienen in: Computational Collective Intelligence
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The Job Shop problem with Time Lags (JSTL) is an important extension of the classical job shop scheduling problem, in that additional constraints of minimum and maximum time lags existing between two successive operations of the same job are added. The objective of this work is to present a distributed approach based on cooperative behaviour and a tabu search metaheuristic to finding the scheduling giving a minimum makespan. The proposed model is composed of two classes of agents: a Supervisor Agent, responsible for generating the initial solution and containing the Tabu Search core, and Resource_Scheduler Agents, which are responsible for moving several operations and satisfaction of some constraints. Good performances of our model are shown through experimental comparisons on benchmarks of the literature.