Partner selection model and soft computing approach for dynamic alliance of enterprises

Abstract

Partner selection is an active research topic in agile manufacturing and supply chain management. In this paper, the problem is described by a 0–1 integer programming with non-analytical objective function. Then, the solution space is reduced by defining the inefficient candidata. By using the fuzzy rule quantification method, a fuzzy logic based decision making approach for the project schedulling is proposed. We then develop a fuzzy decision embedded genetic algorithm. We compare the algorithm with tranditional methods. The results show that the suggested approach can quickly achieve optimal solution for large size problems with high probability. The approach was applied to the partner selection problem of a coal fire power station construction project. The satisfactory results have been achieved.

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