Article ID: | iaor2000654 |
Country: | United Kingdom |
Volume: | 50 |
Issue: | 1 |
Start Page Number: | 85 |
End Page Number: | 94 |
Publication Date: | Jan 1999 |
Journal: | Journal of the Operational Research Society |
Authors: | Gupta A., Reyes-Aldasoro C.C., Ganguly A.R., Lemus G. |
Keywords: | programming: dynamic, neural networks |
This paper proposes a new approach to minimise inventory levels and their associated costs within large geographically dispersed organisations. For such organisations, attaining a high degree of agility is becoming increasingly important. Linear regression-based tools have traditionally been employed to assist human experts in inventory optimisation endeavours; recently, Neural Network (NN) techniques have been proposed for this domain. The objective of this paper is to create a hybrid framework that can be utilised for analysis, modelling and forecasting purposes. This framework combines two existing approaches and introduces a new associated cost parameter that serves as a surrogate for customer satisfaction. The use of this hybrid framework is described using a running example related to a large geographically dispersed organisation.