A novel genetic algorithm for partner selection problem in virtual enterprise

Partner selection is a key problem in VE. Mhimizing risk in partner selection and ensuring the due date of the project are key to ensure the success of the VE. In this paper, a multi-objective optimization model is proposed based on the project that is organized by activity network. The objective is to minimize project failure risk and project cost together with tardy penalty by selecting the optimal combination of ´partner enterprises for all sub-projects. The rules based genetic algorithm (R-CA) and the method using R-CA solution to reduce the search space of the enumeration algorithm are . presented. Compared with the CA without rule and enumeration algorithm, the R-CA has better synthetic performance in both the computation speed and optimality as knowledge about the project is used in the rule of the R-CA. The results indicate that the proposed model and algorithm can obtain satisfactory of the problems.