Abstract
In this paper, we develop two stochastic mixed integers linear programming (SMILP) models for supplier selection under disruption risk considering different capacity, failure probability, uncertain demand and quantity discounts. The suppliers are assumed domestic suppliers and global suppliers. The obtained combinatorial stochastic optimisation problem is formulated as a mixed integer program with conditional value-at-risk technique (CVaR). Numerical examples and computational results are presented. The proposed models can optimise the present problem through an estimated value at risk (VaR) and minimised CVaR simultaneously. The computational results reveal that the proposed models allow the decision maker to make an efficient selection of suppliers under disruption risk. Results also show that the decisions are not univocal because they depend on the risk proneness of the decision maker.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Risk Assessment and Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
