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Ant colony optimization for job shop scheduling using multi-attribute dispatching rules

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This paper proposes a heuristic method based on ant colony optimization to determine the suboptimal allocation of dynamic multi-attribute dispatching rules to maximize job shop system performance (four measures were analyzed: mean flow time, max flow time, mean tardiness, and max tardiness). In order to assure high adequacy of the job shop system representation, modeling is carried out using discrete-event simulation. The proposed methodology constitutes a framework of integration of simulation and heuristic optimization. Simulation is used for evaluation of the local fitness function for ants. A case study is used in this paper to illustrate how performance of a job shop production system could be affected by dynamic multi-attribute dispatching rule assignment.


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Correspondence to Przemysław Korytkowski.

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Korytkowski, P., Rymaszewski, S. & Wiśniewski, T. Ant colony optimization for job shop scheduling using multi-attribute dispatching rules. Int J Adv Manuf Technol 67, 231–241 (2013). https://doi.org/10.1007/s00170-013-4769-4

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  • Ant colony optimization
  • Multi-attribute dispatching rules
  • Discrete-event simulation
  • Dynamic job shop