ehsanifar mohammad

Resource constrained project scheduling problem is one of the most important issues in project planning and management. The objective function of this problem is to minimize the completion time of a project. When there is budget constraint or high risk for investment, using the criteria such as cash flows is so important. The development of computer systems and processors makes it possible to take more assumptions into modeling to obtain robust optimal solution. Recent research has been conducted on multimode resource constrained project scheduling problem with preemptive activities (P-MRCPSP). Assuming preemption of activities causes the model to approach the real-world problems in project scheduling. This assumption may occur due to factors such as equipment failure and shortage of resources. In most of the previous studies, the change in mode of activities was not possible after the discontinuation. In this paper, it is assumed that each activity can continue in various modes of operation after a stop. The developed model aims to minimize project completion time and maximize cash flow of the project, simultaneously. Two algorithms, i.e. Simulated Annealing (SA) and Multiple Objective Particle Swarm Optimization (MOPSO) have been developed to solve the proposed model. The obtained results of these two algorithms show that SA algorithm has the better performance.