Production scheduling by using ACO and PSO techniques

Production scheduling is an important part of the production management in the manufacturing systems area for the reason that its main objective is to increase the productivity and to minimize the operating costs. In this paper it is presented a swarm intelligence approach over the job shop scheduling problem, by using Ant Colony Optimization and Particle Swarm Optimization techniques. Due to the high complexity of this problem an optimal solution, that solves the resources conflicts and minimizes the makespan and total completion time, is difficult to obtain. In this context a comparison between the two implemented techniques is presented in order to evaluate the performance considering different simulation production scenarios.