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Title: A fuzzy-GA decision support system for enhancing postponement strategies in supply chain management
Authors: Tang, CXH
Lau, HCW
Keywords: Supply chain management
Hybrid optimisation algorithms
Issue Date: 2008
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2008, v. 5361, p. 141-150 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
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.
Description: 7th Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 2008, Melbourne, Australia, December 7-10, 2008
ISBN: 978-3-540-89693-7
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-540-89694-4_15
Appears in Collections:Conference Paper

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