Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: A dynamic forward approach
Abstract: The issue resource
over-allocating is a big concern for project engineers in the process of
scheduling project activities. Resource over-allocating drawback is frequently
seen after scheduling of a project in practice which causes a schedule to be
useless. Modifying an over-allocated schedule is very complicated and needs a
lot of efforts and time. In this paper, a new and fast tracking method is
proposed to schedule large scale projects which can help project engineers to
schedule the project rapidly and with more confidence.
Design/methodology/approach: In this article, a forward approach for
maximizing net present value (NPV) in multi-mode resource constrained project
scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF)
is proposed. 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 forward mode. For this
purpose, a Genetic Algorithm is applied to solve.
Findings: The findings show that the proposed method is an effective way
to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The
proposed algorithm is very fast and can schedule experimental cases with 1000
variables and 100 resources in few seconds. The results are then compared with
branch and bound method and simulated annealing algorithm and it is found the
proposed genetic algorithm can provide results with better quality. Then
algorithm is then applied for scheduling a hospital in practice.
Originality/value: The method can be used alone or as a macro in
Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify
resource over-allocated activities after scheduling a project. This can help
project engineers to schedule project activities rapidly with more accuracy in
practice.
Keywords: Multimode Project
Scheduling, Genetic Algorithm, Pre-emptive Constrained Resources, Discounted
Cash Flows
Author: Aidin Delgoshaei, Mohd
Khairol Mohd Ariffin, B. T. Hang Tuah Baharudin
Journal Code: jptindustrigg160013
