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

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 re-sources are considered as pre-emptible. The p...

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Bibliographic Details
Main Authors: Aidin Delgoshaei, Sepehr Esmaeili Hanjani, Amir Hossein Nasiri
Format: Article
Language:English
Published: Growing Science 2019-04-01
Series:Journal of Project Management
Subjects:
Online Access:http://www.growingscience.com/jpm/Vol4/jpm_2019_13.pdf
Description
Summary: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 re-sources 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.
ISSN:2371-8366
2371-8374