Multi-criteria Human Resource Allocation for Optimization Problems Using Multi-objective Particle Swarm Optimization Algorithm

Multi-criteria human resource allocation involves deciding how to divide human resource of limited availability among multiple demands in a way that optimizes current objectives. This paper aims to solve the multi-criteria optimal allocation of human resources issues using multi-objective particle swarm optimization (MOPSO). In this paper, we tackled this problem via a multi-objective decision-making model using a multi-objective PSO. We developed the Mathematical model of human resource optimization allocation using the competency model theory, and then in order to obtain a set of Pareto solutions efficiently, we proposed the multi-objective PSO (MOPSO) approach based on the decision-making model for solving combinatorial optimization problems. According to the proposed method, we applied the MOPSO to seek feasible solutions for the problem. The effectiveness of the proposed algorithm was validated by its application to an illustrative example dealing with multi-objective resource allocation problem.