A heuristic genetic algorithm for subcontractor selection in a global manufacturing environment

Dingwei Wang, Kai Leung Yung, W. H. Ip

Research output: Journal article publicationJournal articleAcademic researchpeer-review

119 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)189-198
Number of pages10
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Issue number2
Publication statusPublished - 1 May 2001


  • Agile manufacturing
  • Fuzzy logic
  • Genetic algorithm (GA)
  • Partner selection
  • Project management
  • Soft computing
  • Virtual enterprise

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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