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

Jens Hartmann (), Thomas Makuschewitz (), Enzo M Frazzon () and Bernd Scholz-Reiter ()
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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

A chapter in Operations Research Proceedings 2012, 2014, pp 533-539 from Springer

Abstract: 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.

Keywords: Continuous Subproblem; Solution Search Space; Binary Dependent Variables; Feasible Offspring; Machine Related Parameters (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-3-319-00795-3_80

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