Enhancing Project Performance: Particle Swarm Optimization for Optimal Budget Allocation and Maintenance Scheduling

This study aims to help project-oriented organizations manage their portfolios and arrive at an optimum budget allocation. In this study, the budget allocation process in a portfolio of projects is mathematically formulated. The interactions between the projects as well as the operational and budget constraints are considered. Then, the optimal budget allocation is determined using the particle swarm optimization algorithm. To evaluate the performance of the proposed approach, it is implemented on a portfolio of maintenance projects. In this article, we will explore the application of PSO in portfolio management and how it can help investors make better investment decisions. According to the results, the operational constraints and budget restrictions will significantly affect the optimum budget allocation solution and consequently the revenue of a portfolio. Lack of access to detailed information about the maintenance schedule of dam projects might be a limitation for future application of the proposed approach. It is believed that the proposed approach provides a powerful and efficient tool of optimal budget allocation in portfolio of projects. This research addresses several shortcomings of previous studies for optimal budget allocation.