A New Model for Optimizing Simultaneously Projects Selection and Resource- Constrained Project Scheduling Problem with particle swarm optimization

In this paper, the problem of selecting and scheduling projects regarding the maximum amount of resource constraints and the net present value of the project is modeled, analyzed and solved. This study shows the condition in which some projects should be performed among all available projects. Decision makers should choose a subset of these projects based on resource constraints in order to maximize final profit. Project selection models usually do not consider project scheduling as a part of selection process. However, except in cases where only one project is active at any time during the project, prioritizing selected projects regardless of their schedule is not optimal. Project scheduling in the level of project activities, increases the complexity of search space and spreads the decision space for selecting a portfolio of projects. Hence, in this study a particle swarm optimization algorithm is developed for solving large scale problems. Finally, in order to validate the quality of the proposed meta-heuristic approach, several test problems have been solved in small and large sizes. The results show the good performance of the presented algorithm.