PSO in 2D-space to solve reactive scheduling problems in FMS to reduce the makespan

Production reactive scheduling considering simultaneous use of machines and AGVs in Flexible Manufacturing Systems (FMS) involves modeling and searching methodology in a wide solution space. Several researches have been using the Genetic Algorithms (GA) as a search method to solve this problem since these algorithms have the capacity of globally exploring the search space and find good solutions quickly. Due to the characteristics of the problem, this paper proposes the use of Particle Swarm Optimization (PSO) to solve reactive scheduling problems with the minimization of makespan in FMS. The proposal was tested in two factory scenarios and validated by comparing its results with those obtained by techniques based on genetic algorithm and adaptive genetic algorithm.