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Exact methods for the robotic cell problem

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Abstract

This paper investigates an exact method for the Robotic Cell Problem. We present a branch-and-bound algorithm which is the first exact procedure specifically designed with regard to this complex flow shop scheduling variant. Also, we propose a new mathematical programming model as well as new lower bounds. Furthermore, we describe an effective genetic algorithm that includes, as a mutation operator, a local search procedure. We report the results of a computational study that provides evidence that medium-sized instances, with up to 176 operations, can be optimally solved. Also, we found that the new proposed lower bounds outperform lower bounds from the literature. Finally, we show, that the genetic algorithm delivers good solutions while requiring short CPU times.

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Acknowledgments

This work was partially supported by the ANR (LMCO project). Dr. Mohamed Haouari would like to thank Fatimah Alnijris Research Chair for Advanced Manufacturing Technology for the financial support provided for this research.

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Authors and Affiliations

  1. UMR CNRS 6599 Heudiasyc, Centre de Recherches de Royallieu, Université de Technologie de Compiègne, Compiègne, France

    Mohamed Kharbeche, Jacques Carlier & Aziz Moukrim

  2. Department of Industrial Engineering, Faculty of Engineering, Ozyegin University, Istanbul, Turkey

    Mohamed Haouari

  3. LISI, National Institute of Applied Sciences and Technology, University of Carthage, Tunis, Tunisia

    Mohamed Kharbeche & Mohamed Haouari

  4. Princess Fatimah Alnijris’ Research Chair for AMT, College of Engineering, King Saud University, Riyadh, Saudi Arabia

    Mohamed Haouari

Authors
  1. Mohamed Kharbeche
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  2. Jacques Carlier
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  3. Mohamed Haouari
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  4. Aziz Moukrim
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Corresponding author

Correspondence to Mohamed Kharbeche.

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Kharbeche, M., Carlier, J., Haouari, M. et al. Exact methods for the robotic cell problem. Flex Serv Manuf J 23, 242–261 (2011). https://doi.org/10.1007/s10696-011-9079-2

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  • DOI: https://doi.org/10.1007/s10696-011-9079-2

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