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A novel decision-making approach for supplier selection under risks

Mokhtar, S., Bahri, P.A., Moayer, S. and James, A. (2017) A novel decision-making approach for supplier selection under risks. Computer Aided Chemical Engineering, 40 . pp. 1267-1272.

Link to Published Version: https://doi.org/10.1016/B978-0-444-63965-3.50213-0
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Abstract

Despite the huge amount of research in the area of supplier selection studying the effect of various risks on a system disruption, less focus has been laid on the proactive management of risk exposure to minimize the undesirable effects of such risks on the system in a timely manner. As such, a real-time monitoring of market indicators gains significance noting that managerial actions can be taken in response to the changes in the business environment in order to prevent disruption effects and limit unfavorable outcomes. This approach is able to dynamically update and so maintain a current perspective on the supplier status. This paper introduces a novel simulation-optimization approach to select a set of suppliers aiming to minimize the supply chain risk and maximize its profit based on a set of risk indicators affecting the supply chain, including financial health, production progression, and quality performance. We analyze the interrelationships among risk sources by modeling the supply chain dynamics through a system dynamics simulation. The results of simulation further apply in a portfolio optimization to maximize the profit and minimize the risks. To demonstrate the application of the model, a case study is developed based on the supply chain of a company with three possible suppliers and one final product. The results of this model support decision makers in determining the optimal supplier selection and order allocation based on their expected profit and their propensity for risk.

Publication Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Elsevier BV
Copyright: © 2017 Elsevier B.V.
URI: http://researchrepository.murdoch.edu.au/id/eprint/40273
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