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Identifying Economic Order Quantities Using Genetic Algorithms

David John Stockton (De Montfort University, Leicester, UK)
Liam Quinn (De Montfort University, Leicester, UK)

International Journal of Operations & Production Management

ISSN: 0144-3577

Article publication date: 1 November 1993

761

Abstract

The ability of traditional economic order quantity (EOQ) models to successfully determine optimum purchase and process batch sizes has declined in recent years. These models are simplistic in nature in that they make assumptions that are no longer valid in practice, in addition, they cannot take into account the wide variety of cost and other factors that influence inventory control decisions. Presents an alternative method for identifying economic batch quantities that uses genetic algorithms (GA) based on the underlying mathematical processes that control the reproduction of genes within biological species. Using genetic algorithms it is possible to successfully deal with complex inventory situations and there are no limits on the type and number of variables that can be used to influence the batch‐sizing decision.

Keywords

Citation

Stockton, D.J. and Quinn, L. (1993), "Identifying Economic Order Quantities Using Genetic Algorithms", International Journal of Operations & Production Management, Vol. 13 No. 11, pp. 92-103. https://doi.org/10.1108/01443579310046463

Publisher

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MCB UP Ltd

Copyright © 1993, MCB UP Limited

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