A two-phased evolutionary approach for intelligent task assignment & scheduling

In this paper, a two-phased evolutionary approach that integrates particle swarm optimization (PSO) and genetic algorithm (GA) is proposed to help assigning and scheduling maintenance crews to maintenance tasks automatically. The validity of the proposed system is verified experimentally. Results from the experiments indicate that the two-phased integration of PSO and GA in the proposed system is a robust and effective intelligent planning mechanism to help make decisions for task assignment and scheduling with higher efficiency.