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http://dx.doi.org/10.11627/jkise.2017.40.4.112

A Multi-Phase Decision Making Model for Supplier Selection Under Supply Risks  

Yoo, Jun-Su (Department of Industrial and Management Systems Engineering, College of Engineering, Kyung Hee University)
Park, Yang-Byung (Department of Industrial and Management Systems Engineering, College of Engineering, Kyung Hee University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.40, no.4, 2017 , pp. 112-119 More about this Journal
Abstract
Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.
Keywords
Supply Risks; Supplier Selection; Rule-based Expert System; TOPSIS; Pareto Optimal Suppliers;
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Times Cited By KSCI : 1  (Citation Analysis)
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