A fuzzy-GA decision support system for enhancing postponement strategies in supply chain management

Abstract

This paper aims to propose a knowledge-based Fuzzy - GA Decision Support System with performance metrics for better measuring postponement strategies. The Fuzzy - GA approach mainly consists of two stages: knowledge representation and knowledge assimilation. The relevant knowledge of deciding what type of postponement strategies to adopt is encoded as a string with a fuzzy rule set and the corresponding membership functions. The historical data on performance measures forming a combined string is used as the initial population for the knowledge assimilation stage afterwards. GA is then further incorporated to provide an optimal or nearly optimal fuzzy set and membership functions for related performance measures. The originality of this research is that the proposed system is equipped with the ability of assessing the loss caused by discrepancy away from the different supply chain parties, and therefore enabling the identification of the best set of decision variables.