Traditionally, project scheduling and material planning have been treated independently. In this research, a mixed integer programming model is presented to integrate project scheduling and materials ordering problems. The goal is to minimize the total material holding and ordering costs. In addition, an efficient metaheuristic algorithm is proposed to solve the model. The proposed algorithm is computationally tested, the results are analyzed, and conclusions are given.
In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.