This paper is about the Resource-Constrained Project Scheduling Problem) RCPSP) which is one of the most important problems in last three decades and many researchers have paid attention to it and have reached useful results. In this paper, to cope with uncertainty issue, the RCPSP is studied under fuzzy environment where activity times are assumed to be fuzzy numbers. For this problem with fuzzy numbers as activity times, a linear mathematical programming model is presented. The objective function of the model is minimizing the completion time of project. Since the activity times are fuzzy numbers, finish time is also a fuzzy number. Hence, the model is transformed to a crisp multi-objective linear programming model. To illustrate the solution method, a numerical example is solved under both fuzzy and crisp environment and the results are compared. To prove the efficiency of the proposed method the results of the proposed solution method, some benchmark problems obtained from PSPLIB are utilized.

The design of supply chain (SC) networks has attracted more attention in recent years according to business and environmental factors.in this paper a multi objective supply chain network design model aims to minimize network costs while satisfying the desired service level, is presented. A fuzzy goal programming (FGP) solution approach based on fuzzy membership function concept is developed to minimize costs and amount of investment while obtain maximum service level. Numerical experiments are conducted to test the efficiency of proposed solution method.