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A hybrid model based on dynamic programming, neural networks, and surrogate value for inventory optimisation applications
journal contribution
posted on 2023-06-08, 11:21 authored by Constantino C Reyes-Aldasoro, A R Ganguly, G Lemus, A GuptaThis 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.
History
Publication status
- Published
Journal
Journal of the Operational Research SocietyISSN
0160-5682Publisher
Palgrave MacmillanExternal DOI
Issue
1Volume
50Page range
85-94Department affiliated with
- Engineering and Design Publications
Notes
169QR Times Cited:1 Cited References Count:32Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-04-24Usage metrics
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