A genetic algorithm for scheduling multimode resource-constrained project problem in the presence of preemptive resources

Abstract

Article history: Received: January 8 2019 Received in revised format: January 27 2019 Accepted: March 19 2019 Available online: March 19 2019 In this paper, a backward approach is proposed for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF). The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in backward mode. For this purpose, a Genetic Algorithm is applied to solve experimental cases with 50 variables and the results are compared with forward serial programming method. The remarkable results reveal that the backward approach is an effective way to maximize NPV in MRCPSP-DC while activity splitting is allowed. The algorithm is flexible enough to be used in real project. © 2019 by the authors; licensee Growing Science, Canada.