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KBLS: A prototype knowledge-based system for the selection of lot-sizing models

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Abstract

Research in experimental simulation of multi-stage inventory systems shows that a poor choice of lot-sizing heuristics has a significant degree of cost penalty and schedule instability. A realistic approach to a multi-stage system is to choose a suitable technique for a certain special circumstance rather than trying for a single best heuristic covering all cases. To avoid serious cost penalties and high schedule instability caused by inferior techniques, knowledge-based system technology could help practitioners to make a sensible choice of heuristics. In this paper, we develop a prototype knowledge-based system whose aim is to provide an acceptable lot-size schedule in a limited time which would hopefully lead to a good master production schedule.

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Authors and Affiliations

  1. Department of Management, University of Louisville, 40292, Louisville, KY, USA

    Yash P. Gupta

  2. Department of Actuarial and Management Sciences, University of Manitoba, R3T 2N2, Winnipeg, MB, Canada

    Ying K. Keung

Authors
  1. Yash P. Gupta
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  2. Ying K. Keung
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Gupta, Y.P., Keung, Y.K. KBLS: A prototype knowledge-based system for the selection of lot-sizing models. J Intell Manuf 2, 199–211 (1991). https://doi.org/10.1007/BF01471107

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  • DOI: https://doi.org/10.1007/BF01471107

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