Supply chain outsourcing risk using an integrated stochastic-fuzzy optimization approach

Authors:
Dexiang Wu;Desheng Dash Wu;Yidong Zhang;David L. Olson
Affiliations:
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada M5S 3G8;RiskLab, University of Toronto, Toronto, Ontario, Canada M5S 3G8 and School of Management, University of Science and Technology of China, 96 Jinzhai, Hefei, Anhui 230026, PR China;SUNY, Buffalo, Department of Industrial and System Engineering, USA;Department of Management, University of Nebraska, Lincoln, NE 68588-0491, USA
Venue:
Information Sciences: an International Journal
Year:
2013

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Abstract

A stochastic fuzzy multi-objective programming model is developed for supply chain outsourcing risk management in presence of both random uncertainty and fuzzy uncertainty. Utility theory is proposed to treat stochastic data and fuzzy set theory is used to handle fuzzy data. An algorithm is designed to solve the proposed integrated model. The new model is solved using the proposed algorithm for a three stage supply chain example. Computation suggests an analysis of risk averse and procurement behavior, which indicates that a more risk-averse customer prefers to order less under uncertainty and risk. Trade-off game analysis yields supported points on the trade-off curve, which can help decision makers to identify proper weighting scheme where Pareto optimum is achieved to select preferred suppliers.