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

  • Przemysław Korytkowski
  • Szymon Rymaszewski
  • Tomasz Wiśniewski
Open Access


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.


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


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Copyright information

© The Author(s) 2013

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  • Przemysław Korytkowski
    • 1
  • Szymon Rymaszewski
    • 1
  • Tomasz Wiśniewski
    • 2
  1. 1.Department of Computer ScienceWest Pomeranian University of Technology in SzczecinSzczecinPoland
  2. 2.Faculty of Management and Economics of ServicesUniversity of SzczecinSzczecinPoland

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