Resilient supplier selection through fuzzy-topsis

Abstract

In resent business world, supply chain management (SCM) has become a key issue of conceptual and empirical research. As a fundamental decision-making for mangers, the quality of supplier performance not only affects the downstream business, but also determines the success of the whole supply chain. Therefore, resiliency planning is becoming a crucial strategic issue to choosing suitable suppliers in the supply chain; it directly impacts the benefits for managers of organizations. The resilient supplier selection is a complex multi-criteria problem in both quantitative and qualitative factors which may be in conflict and may also be uncertain. So in this context fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method helps to deal with inaccurate, incomplete and imperfect information to some extent. To avoid complicated aggregation of fuzzy numbers, these weighted ratings are defuzzified into crisp values by the ranking method of mean of removals. A closeness coefficient is defined to determine the ranking order of alternatives by calculating the distances to both fuzzy positive ideal solution and fuzzy negative ideal solution. A case study is proposed for resilient supplier evaluation in an automobile parts manufacturing industry in India.