Title: Optimising resource-constrained project probabilistic scheduling problem through a combination of simulation and meta-heuristic algorithm (case study: Govah Sanat Company)

Authors: Maryam Ghasemifard; Sayed Shahab Amelian

Addresses: Department of Industrial Engineering, Faculty of Engineering, Lenjan Branch, Islamic Azad University, Esfahan, Iran ' Department of Mechanical Engineering, Shahinshahr Branch, Islamic Azad University, Shahinshahr, Iran

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.

Keywords: project management; optimisation; meta-heuristic algorithms; probabilistic scheduling; Monte Carlo simulation.

DOI: 10.1504/IJPOM.2022.124132

International Journal of Project Organisation and Management, 2022 Vol.14 No.2, pp.126 - 143

Received: 26 Sep 2020
Accepted: 15 Mar 2021
Published online: 14 Jul 2022 *

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