Fuzzy Chance-Constrained Project Portfolio Selection Model Based on Credibility Theory

This paper discusses a fuzzy chance-constrained project portfolio selection problem based on credibility theory. Risk of project portfolio is measured using conditional value at risk (CVaR) approach. The proposed model maximizes the expected fuzzy net present value (FNPV) subject to credibilistic chance constraint (CCC) of CVaR. We transform the chance-constrained model into deterministic model when the investment cost and return are characterized by triangular and trapezoidal fuzzy numbers. An improved genetic algorithm (GA) is designed to solve this problem. Two numerical examples with different types of membership function are also given to illustrate the modeling idea of the paper and to demonstrate the effectiveness of the proposed algorithm.