Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25638
Title: A heuristic genetic algorithm for subcontractor selection in a global manufacturing environment
Authors: Wang, D
Yung, KL
Ip, WH
Keywords: Agile manufacturing
Fuzzy logic
Genetic algorithm (GA)
Partner selection
Project management
Soft computing
Virtual enterprise
Issue Date: 2001
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews, 2001, v. 31, no. 2, p. 189-198 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews 
Abstract: In this paper, we present an investigation of how partner selection problems may be optimized by the use of a precedence network of subprojects. At the start, the problem is described by a model with the subscript-type of variables and nonanalytical objective function. It cannot be solved by general mathematical programming methods. By using the fuzzy rule quantification method, a fuzzy logic based decision making approach for the project scheduling is proposed. We then develop a fuzzy decision embedded heuristic genetic algorithm (GA/FD) to find the solution for partner selection. The approach was demonstrated by the use of an experimental example drawn from a coal fire power station construction project. The results show us that the suggested approach is possible to quickly achieve optimal solution for large size problems.
URI: http://hdl.handle.net/10397/25638
ISSN: 1094-6977
DOI: 10.1109/5326.941842
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