Optimizing Competency-Based Human Resource Allocation in Construction Project Scheduling: A Multi-Objective Meta-Heuristic Approach

Effective allocation of human resources to project activities is crucial in optimizing project schedules and resource utilization. This paper addresses the challenge of competency-based workforce allocation in construction project scheduling by integrating multi-criteria decision-making with meta-heuristic optimization. A three-objective mathematical planning model aimed at minimizing project completion time, reducing implementation costs, and enhancing workforce competency is proposed. By leveraging expert opinions and multi-criteria decision-making techniques the relevant competency criteria are identified and prioritized. Our approach involves solving a sample problem precisely using GAMS software and developing two meta-heuristic algorithms—Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). The algorithms' parameters were optimized using Taguchi design techniques to ensure robust performance. The effectiveness of our proposed methods is validated by comparing their results with exact solutions and conducting extensive tests on large-scale problems. The results demonstrate that both meta-heuristic algorithms effectively address the competency-based allocation challenge, with NSGA-II showing superior performance in achieving optimal solutions. This study highlights the potential of integrating competency-based approaches with advanced optimization techniques to enhance project management in construction.