Journal article
Inventory strategy development under supply disruption risk
Computers & Industrial Engineering, Vol.161, Article 107662
2021
Abstract
This paper proposes a multi-period decision-making framework that enables procurement managers to develop an optimal supply inventory strategy under uncertain supply conditions. The framework draws on financial options valuation techniques by adopting the view of a procurement manager facing several uncertainties, while seeking to maximise its profit by exercising its flexibility to procure supplies and use inventories. Given the multitude of uncertain variables influencing inventory management decision in practice, the model is developed to remain robust to the inclusion of several underlying stochastic variables; it uses an American options valuation method and a least squares Monte Carlo simulation technique to solve the underlying dynamic programming problem. To demonstrate the application of the developed framework, a case study is presented based on data from a dairy supply chain. The case study explores the decision problem in several scenarios, showing how a decision-maker’s perception of product demand and supply price uncertainties, expectations over the timing of a supply disruption, discount rate, price shocks and disruption duration can be suitably incorporated into the decision-making framework.
Details
- Title
- Inventory strategy development under supply disruption risk
- Authors/Creators
- S. Mokhtar (Author/Creator)P.A. Bahri (Author/Creator)M. Shahnazari (Author/Creator)
- Publication Details
- Computers & Industrial Engineering, Vol.161, Article 107662
- Publisher
- Elsevier
- Identifiers
- 991005541597707891
- Copyright
- © 2021 Elsevier Ltd
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.84 Supply Chain & Logistics
- 4.84.260 Supply Chain Optimization
- Web Of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Industrial
- ESI research areas
- Computer Science