Robust Optimization Model for Project Scheduling Problem with Resource Constraints

Document Type : Original Article

Authors

Industrial Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Accurate management of projects is necessary to keep companies competitive. The resource-constrained project scheduling problem (RCPSP) includes activities that must be planned according to priority and resource constraints, and minimize the project completion time. This has become a well-known standard problem in the field of project planning, and various formats of the initial RCPSP have been developed. On the other hand, due to the inherent uncertainty of the project environment, which causes uncertainty in the time and resource parameters, examining such issues considering this uncertainty at the same time as the complexity of the issue is very necessary. The purpose of this research is to provide an approach for the allocation of limited resources in the multi-project scheduling problem, with the uncertainty of the duration of the project activities. Also, in the space of this problem, the selection of the supplier of resources has been considered as the objectives of the problem. After introducing the stable model based on the scenario, the answers were analyzed using the meta-heuristic algorithm of multi-objective genetic, and the results show that with an increase in the cost of providing resources, the cost of the whole project increases, but this increase is more in the fourth scenario. This increase is not only in the cost, but also leads to an increase in the project time. On the other hand, the risk of supplier failure can affect the cost and time of the project. As the risk of supplier failure increases, the cost increases and the highest increase occurs in scenario 1, while in scenario 3, the lowest cost increase occurs due to the risk of supplier failure.

Keywords

Main Subjects

References

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Journal of Computational Methods in Engineering
Volume 44, Issue 2 - Serial Number 30
December 2025
Pages 127-149

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