A multiobjective optimization framework for optimal selection of supplier portfolio

Abstract

Supplier selection problem has been a typical concern of optimization where good supplier selection is essential for firms in the context of supply chain management. If a firm networks with different suppliers, each one having its own advantages over the others, then there is great opportunity to reduce a firm’s risk arising from supply concentration and also to provide it with the opportunity to leverage its comparative strength. In this paper, we propose a new approach referred to as Supplier Portfolio Optimization (SPO) that improves the state of the art of supplier selection by incorporating the benefits of supplier diversification using the trade-offs between the criteria of expected unit price, expected score of quality and expected score of delivery. We present three different optimization models with interval coefficients to model the uncertain SPO problem corresponding to optimistic, pessimistic and combination strategies. Further, using lower and upper bonds for fractions of order quantity, we ensure supplier portfolio diversification and also avoidance of the situation of impractical fraction of quantity ordered. Numerical experiments conducted on a dataset of a multinational firm are provided to demonstrate the applicability and efficiency of the SPO models to real-world applications of supplier selection.

Keywords:

• multiobjective optimization
• interval programming
• supplier selection
• portfolio optimization
• supply chain management
• diversification

AMS Subject Classifications:

• 90C29
• 90C90
• 91G10
• 91B32

Acknowledgement

We are thankful to the Editor-in-Chief, Associate Editor and anonymous referees for their valuable comments and suggestions to improve the presentation of this paper.

Notes

The research of the first author was partially supported by NSC grant [number NSC 102-2221-E-182-040-MY3]. The second author acknowledges the Research and Development Grant received from the University of Delhi, Delhi, India. The third author acknowledges financial support received from UGC, New Delhi, India.