A Novel Analysis Model for Project Risk Management

Risk management of engineering project is a complicated uncertainty problem. Based on the theory of set pair analysis (SPA), stochastic simulation of triangular fuzzy numbers, herein, a novel analysis model for the project risk management was discussed. A concept of multi-element connection number of the set pair was introduced to express the hierarchy and fuzziness of membership between the evaluation indexes and risk classification standard of risk factor. Moreover, the triangular fuzzy number simulated by Monte-Carlo method was presented to depict the changing process and fuzziness of component coefficients of discrepancy degree. The predicted risk grade of risk factor and corresponding confidence degree are used to select the risk grade of risk factor according to maximum subordination principle. Combined with the weight of each risk factor, the integrated risk degree was calculated to assess the risk grade of engineering project. Finally, a practical example was described to confirm and to compare with the extension method. The results show that the proposed model is more feasible and easy to operate, and the result is good.