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Multi Agent Model Based on Chemical Reaction Optimization for Flexible Job Shop Problem

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Computational Collective Intelligence

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

Abstract

The Flexible Job Shop Problem (FJSP) is an extension of classical job shop problem such that each operation can be processed on different machine and its processing time depends on the machine used. This paper proposes a new multi-agent model based on the meta-heuristic Chemical Reaction Optimization (CRO) to solve the FJSP in order to minimize the maximum completion time (makespan). Experiments are performed on benchmark instances proposed in the literature to evaluate the performance of our model.

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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

    Olfa Belkahla Driss

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

    Bilel Marzouki & Olfa Belkahla Driss

Authors
  1. Bilel Marzouki
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  2. Olfa Belkahla Driss
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Corresponding author

Correspondence to Bilel Marzouki .

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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Marzouki, B., Belkahla Driss, O. (2015). Multi Agent Model Based on Chemical Reaction Optimization for Flexible Job Shop Problem. 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_3

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  • DOI: https://doi.org/10.1007/978-3-319-24069-5_3

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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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