Article ID: | iaor1994838 |
Country: | United Kingdom |
Volume: | 13 |
Issue: | 11 |
Start Page Number: | 92 |
End Page Number: | 103 |
Publication Date: | Nov 1993 |
Journal: | International Journal of Operations & Production Management |
Authors: | Stockton D.J., Quinn L. |
Keywords: | genetic algorithms |
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 These models are simplistic in nature in that they make assumptions that are no longer valid in practice, in addition, they cannot take into account the wide variety of cost and other factors that influence inventory control decisions.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 process 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.