Paper Info
Title
A Fuzzy-guided Genetic Algorithm for Quality Enhancement in the Supply Chain
Abstract
To respond to the globalization and fierce competition, manufacturers gradually realize the challenge of demanding customers who strongly seek for products of high-quality and low-cost, which implicitly calls for the quality improvement of the products in a cost-effective way. Traditional methods focused on specified process optimization for quality enhancement instead of emphasizing the organizational collaboration to ensure qualitative performance. This paper introduces artificial intelligence (AI) approach to attain quality enhancement by automating the selection of process parameters within the supply chain. The originality of this research is providing an optimal configuration of process parameters along the supply chain and delivering qualified outputs to raise customer satisfaction.
Year
Venue
Keywords
2009
ICEIS 2009 : PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL AIDSS
Global optimization,Supply chain management,Advanced manufacturing technologies
Field
DocType
Citations 
Data mining,Computer science,Fuzzy logic,Quality enhancement,Supply chain,Genetic algorithm
Conference
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Cassandra X. H. Tang152.81
Henry C. W. Lau230133.27