Genetic algorithm solution for a risk-based partner selection problem in a virtual enterprise

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

Research output: Journal article publicationJournal articleAcademic researchpeer-review

179 Citations (Scopus)

Abstract

Dynamic alliance and virtual enterprise (VE) are essential components of global manufacturing. Minimizing risk in partner selection and ensuring the due date of a project are the key problems to overcome in VE, in order to ensure success. In this paper, a risk-based partner selection problem is described and modeled. Based on the concept of inefficient candidate, the solution space of the problem is reduced effectively. By using the characteristics of the problem considered and the knowledge of project scheduling, a rule-based genetic algorithm (R-GA) with embedded project scheduling is developed to solve the problem. The performance of this algorithm is demonstrated by a problem encountered in the construction of a stadium station and the experimental problems of different sizes. The results of this trial demonstrate the real life capability of the algorithm. With the rapidly increasing competitiveness in global manufacturing area, a dynamic alliance VE approach is needed in order to meet the market's requirements for quality, responsiveness, and customer satisfaction. As the VE environment continues to grow in size and complexity, the importance of managing such complexity increases. Once the dynamic alliance is to be established, how to select an appropriate partner becomes the key problem and has attracted much research attention recently. For the partner selection problem, in addition to cost, due date and the precedence of sub-project, the risk of failure of the project is another important factor need to be considered. Therefore, an effective approach that can actually deal with the risk-based partner selection problem is a major concern in VEs. Qualitative analysis methods are commonly used to deal with the partner selection problem in many researches. However, quantitative analysis methods for partner selection are still a challenges to VEs. Therefore, there is a need to formulate mathematical models and propose optimization methods for VEs to make decision on partner selection. In this paper, a risk-based partner selection problem is described and formulated where risk of failure, due date and the predence of sub-project are concerned. Based on the concept of inefficient candidate, the solution space of the problem is reduced first. Then an R-GA with embedded project scheduling is developed for solving the problem where fuzzy factors-based rules are proposed in order to modify the partner selection according to different situations in the evaluation process of genetic algorithm by using the characteristics of the considered problem and the knowledge of project scheduling.
Original languageEnglish
Pages (from-to)213-231
Number of pages19
JournalComputers and Operations Research
Volume30
Issue number2
DOIs
Publication statusPublished - 1 Feb 2003

Keywords

  • Genetic algorithm
  • Global manufacturing
  • Partner selection
  • Project management
  • Virtual enterprise

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research

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