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MATS–JSTL: A Multi-Agent Model Based on Tabu Search for Job Shop Problem with Time Lags

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Computational Collective Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9329))

Abstract

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.

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Author information

Authors and Affiliations

  1. Stratégies d’Optimisation et Informatique IntelligentE, High Institute of Management, University of Tunis, 41, Street of Liberty Bouchoucha-City CP-2000-Bardo, Tunis, Tunisia

    Belkahla Driss Olfa

  2. Higher Business School of Tunis, University of Manouba, Manouba, Tunisia

    Madiha Harrabi & Belkahla Driss Olfa

Authors
  1. Madiha Harrabi
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  2. Belkahla Driss Olfa
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Corresponding author

Correspondence to Madiha Harrabi .

Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Núñez

  2. Wrocław University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Computer Science Department, Universidad Autónoma De Madrid, Madrid, Spain

    David Camacho

  4. Wrocław University of Technology, Wroclaw, Poland

    Bogdan Trawiński

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Harrabi, M., Olfa, B. (2015). MATS–JSTL: A Multi-Agent Model Based on Tabu Search for Job Shop Problem with Time Lags. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-24069-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24068-8

  • Online ISBN: 978-3-319-24069-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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