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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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References

  1. Azzouz, A., Ennigrou, M., Jlifi, B., Ghédira, K.: Combining tabu search and genetic algorithm in a multi-agent system for solving flexible job shop problem. In: Mexican International Conference on Artificial Intelligence (2012)

    Google Scholar 

  2. Bagheri, A., Zandieh, M., Mahdavi, I., Yazdani, M.: An artificial immune algorithm for the flexible job-shop scheduling problem. Future Generation Computer Systems 26(4), 533–541 (2010)

    Article  Google Scholar 

  3. Brandimarte, P.: Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research 4(1–4), 157–183 (1993)

    Article  MATH  Google Scholar 

  4. Bruker, P., Schlie, R.: Job-shop scheduling with multipurpose machines. Computing 45, 369–375 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chambers, J.B.: Classical and Flexible Job Shop Scheduling by Tabu Search. PhD thesis, University of Texas at Austin, Austin, U.S.A (1996)

    Google Scholar 

  6. Dauzère-Pérès, S., Paulli, J.: An Integrated Approach for Modeling and Solving the General Multiprocessor Job Shop Scheduling Problem using Tabu Search. Annals of Operations Research 70(3), 281–306 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  7. Ennigrou, M., Ghédira, K.: Solving flexible job shop scheduling with a multi-agent system and tabu search. In: Procs. 6th Int. J. Conf. on International Conference on Enterprise Information Systems, Porto, Portugal, vo. l2, pp. 22−28 (2004)

    Google Scholar 

  8. Fattahi, P., Saidi Mehrabad, M., Jolai, F.: Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. Journal of Intelligent Manufacturing 18(331–342), 2007 (2007)

    Google Scholar 

  9. Garey, E.L., Johnson, D.S., Sethi, R.: The Complexity of Flow-shop and Job-shop scheduling. Mathematics of Operations Research 1, 117–129 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  10. Jin, X., Lam, A., li, V.: Chemical Reaction Optimization for the Grid Scheduling Problem. IEEE ICC (2010)

    Google Scholar 

  11. Jun, L., Quan-ke, P.: Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity. Applied Soft Computing 12, 2896–2912 (2012)

    Article  Google Scholar 

  12. Kacem, I., Hammadi, S., Borne, P.: Approach by Localization and Multi-Objective Evolutionary Optimization for Flexible Job Shop Scheduling Problems. IEEE Trans. Systems, Man and Cybernetics 32(1), 1–13 (2002)

    Article  MATH  Google Scholar 

  13. Lam, A., Li, V.: Chemical-reaction-inspired metaheuristic for optimization. IEEE Transactions on Evolutionary Computation 14 (2010)

    Google Scholar 

  14. Mastrolilli, M., Gambardella, L.M.: Effective neighborhood functions for the flexible job shop problem. Journal of Scheduling (2000)

    Google Scholar 

  15. Motaghedi-larijani, A., Sabri-laghaie, K., Heydari, M.: Solving Flexible Job Shop Scheduling with Multi Objective Approach. International Journal of Industrial Engineering and Production Research 21(4), 197–209 (2010)

    Google Scholar 

  16. Nouri, H.E., Belkahla Driss, O., Ghedira, K.: Genetic algorithm combined with tabu search in a holonic multiagent model for flexible job shop scheduling problem. In: 17th International Conference on Enterprise Information Systems (ICEIS) (2015)

    Google Scholar 

  17. Ponnambalam, S.G., Aravindan, P., Rajesh, S.V.: A Tabu Search Algorithm for Job Shop Scheduling. International Journal of Advanced Manufacturing Technology (2000)

    Google Scholar 

  18. Saad, I., Boukef, H., Borne, P.: The comparison of criteria aggregative approaches for the multi-objective optimization of flexible job-shop scheduling problems. In: Fourth Conference on Management and Control of Production and Logistics, MCPL 2007, pp. 603−608, 2007

    Google Scholar 

  19. Wannaporn, T., Thammano, A.: Modified Genetic Algorithm for Flexible Job-Shop Scheduling Problems. Procedia Computer Science 12, 122–128 (2012)

    Article  MATH  Google Scholar 

  20. Zhang, H., Gen, M.: Multi stage based genetic algorithm for flexible job shop scheduling problem. Journal of Complexity International 11, 223–232 (2005)

    Google Scholar 

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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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