GA–SA/CPM/Markov based dynamic risk-management planning for virtual enterprises

A virtual enterprise (VE) is always in an environment with unpredictable change and dynamic markets. Therefore, a VE is more susceptible to risks. Minimizing risk in the operation of a project and ensuring success are major issues to concern in VEs. This paper develops a novel three-level dynamic risk-management planning model for VEs focusing on project organization mode and dynamic features of risk with the objective to maximize the completion probability under the constraints of cost, due date, and quality. The first level adopts non-linear integer programming techniques, the second level is about risk evaluation for the whole project based on network analysis, and the third level is on a Markov process based single process risk evaluation. An algorithm of integrated genetic algorithm plus simulated annealing/critical path method/Markov (GA–SA/CPM/Markov) is then designed to solve the problem and compared with GA and SA respectively. Experimental results show that the proposed algorithm is effective and the three-level model can deal with dynamic risks for VEs.