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A Genetic Algorithm for the Integrated Scheduling of Production and Transport Systems

In: Operations Research Proceedings 2012

Author

Listed:
  • Jens Hartmann

    (BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen)

  • Thomas Makuschewitz

    (BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen)

  • Enzo M Frazzon

    (Federal University of Santa Catarina (UFSC))

  • Bernd Scholz-Reiter

    (BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen)

Abstract

The integrated scheduling of production and transport systems is a NP-hard mixed-integer problem. This paper introduces a genetic algorithm (GA) that addresses this problem by decomposing it into combinatorial and continuous subproblems. The binary variables of the combinatorial subproblem form the chromosomes of each individual. Knowledge-based evolutionary operators are deployed for reducing the solution search space. Furthermore, dependent binary variables are identified which can be efficiently determined rather by a local search than by the evolutionary process. Then, in the continuous subproblem, for fixed binary variables, the optimization problem turns into a linear program that can be efficiently solved, so that the fitness value of an individual is determined.

Suggested Citation

  • Jens Hartmann & Thomas Makuschewitz & Enzo M Frazzon & Bernd Scholz-Reiter, 2014. "A Genetic Algorithm for the Integrated Scheduling of Production and Transport Systems," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 533-539, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-00795-3_80
    DOI: 10.1007/978-3-319-00795-3_80
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