Optimising resource-constrained project probabilistic scheduling problem through a combination of simulation and meta-heuristic algorithm (case study: Govah Sanat Company) Online publication date: Thu, 14-Jul-2022
by Maryam Ghasemifard; Sayed Shahab Amelian
International Journal of Project Organisation and Management (IJPOM), Vol. 14, No. 2, 2022
Abstract: A project scheduling problem can be identified as scheduling a set of activities and allocating different resources to these activities in a way that optimises the problem criteria. The objective in resource-constrained project scheduling problem is the allocation of resources or a set of resources with limited capacity to project activities considering prerequisite relations in order to optimise predetermined goals. In this study, a resource-constrained project scheduling problem has been investigated in the case where times of the activities are probabilistic and a combination of Monte Carlo simulation method and meta-heuristic algorithms has been used to analyse this problem. Finally, an optimal scheduling has been presented to minimise project completion time. In this study, a real sample consisting of 17 activities has been used considering prerequisite relations, with manpower and machinery as its resources. This problem has been explored through Montecarlo-PSO and Montecarlo-SA methods, and the results have shown that the Montecarlo-PSO method converges faster to the optimal solution.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Project Organisation and Management (IJPOM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com