Optimal project selection with random fuzzy parameters

This paper proposes a practical tool of incorporating random fuzzy uncertainty into project selection – when there are some projects available for investment, which ones should the investor choose. In the paper, investment outlays and annual net cash flows of available projects are regarded as random fuzzy variables. Net present value method is employed, and two types of zero–one integer chance-constrained model with random fuzzy parameters are provided. Since it is hard to analytically solve the proposed random fuzzy programming problems, a hybrid intelligent algorithm integrating genetic algorithm and random fuzzy simulation is designed. Numerical examples are also presented to illustrate the modelling idea and to show the effectiveness of the proposed algorithm.