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 These models are simplistic in nature in that they make assumptions that are no longer valid in practice, in addition,they cannot take into account the wide variety of cost and other factors that influence inventory control decisions.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.
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1 November 1993
Research Article|
November 01 1993
Identifying Economic Order Quantities Using Genetic Algorithms Available to Purchase
David John Stockton;
David John Stockton
De Montfort University, Leicester, UK
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Liam Quinn
Liam Quinn
De Montfort University, Leicester, UK
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Publisher: Emerald Publishing
Online ISSN: 1758-6593
Print ISSN: 0144-3577
© MCB UP Limited
1993
International Journal of Operations & Production Management (1993) 13 (11): 92–103.
Citation
Stockton DJ, Quinn L (1993), "Identifying Economic Order Quantities Using Genetic Algorithms". International Journal of Operations & Production Management, Vol. 13 No. 11 pp. 92–103, doi: https://doi.org/10.1108/01443579310046463
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