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

Author

Listed:
  • Maryam Ghasemifard
  • Sayed Shahab Amelian

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.

Suggested Citation

  • Maryam Ghasemifard & Sayed Shahab Amelian, 2022. "Optimising resource-constrained project probabilistic scheduling problem through a combination of simulation and meta-heuristic algorithm (case study: Govah Sanat Company)," International Journal of Project Organisation and Management, Inderscience Enterprises Ltd, vol. 14(2), pages 126-143.
    • Handle: RePEc:ids:ijpoma:v:14:y:2022:i:2:p:126-143
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