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Optimization tool for short-term production planning and scheduling

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  • Józefowska, J.
  • Zimniak, A.

Abstract

A decision support system for short-term production planning and scheduling is presented. The system consists of three modules: an expert system module, an optimization module and a dialog module. The rules defined in the expert module are used to reduce the space searched by the multicriteria genetic algorithm implemented in the optimization module. A set of experiments showed that reducing the search space increases the efficiency of the applied heuristics. Finally, the dialog module supports the decision maker in choosing the best compromise solution from the set of potentially Pareto-optimal solutions generated by the optimization module.

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  • Józefowska, J. & Zimniak, A., 2008. "Optimization tool for short-term production planning and scheduling," International Journal of Production Economics, Elsevier, vol. 112(1), pages 109-120, March.
    • Handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:109-120
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    Cited by:

    1. Xue, Guisen & Felix Offodile, O. & Zhou, Hong & Troutt, Marvin D., 2011. "Integrated production planning with sequence-dependent family setup times," International Journal of Production Economics, Elsevier, vol. 131(2), pages 674-681, June.
    2. Banaszak, Z.A. & Zaremba, M.B. & Muszynski, W., 2009. "Constraint programming for project-driven manufacturing," International Journal of Production Economics, Elsevier, vol. 120(2), pages 463-475, August.
    3. Duvivier, D. & Meskens, N. & Ahues, M., 2013. "A fast multicriteria decision-making tool for industrial scheduling problems," International Journal of Production Economics, Elsevier, vol. 145(2), pages 753-760.
    4. Meyr, Herbert & Mann, Matthias, 2013. "A decomposition approach for the General Lotsizing and Scheduling Problem for Parallel production Lines," European Journal of Operational Research, Elsevier, vol. 229(3), pages 718-731.
    5. Simon Thevenin & Nicolas Zufferey & Rémy Glardon, 2017. "Model and metaheuristics for a scheduling problem integrating procurement, sale and distribution decisions," Annals of Operations Research, Springer, vol. 259(1), pages 437-460, December.
    6. Chimunhu, Prosper & Topal, Erkan & Ajak, Ajak Duany & Asad, Waqar, 2022. "A review of machine learning applications for underground mine planning and scheduling," Resources Policy, Elsevier, vol. 77(C).

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