A risk programming model based on Markov process in a virtual enterprise

Virtual enterprise is becoming a production form of project organization. Minimizing risk in VE and ensuring success are the key problems to overcome. In this paper, in view of different risk effects from stochastic completion time choices of sub-projects , a risk programming model based on Markov process is presented. A genetic algorithm (GA) for this problem with embedded program evaluation and review technique (PERT) is developed to solve this problem. The performance of this algorithm is demonstrated by a case and the experimental problems of different sizes. The results of this trial demonstrate the real life capability of the algorithm.