Scheduling of Flow Shop Production Systems with Particle Swarm Optimization

This article proposes a decision-making algorithm as an optimization tech-nique based on a particle swarm (particle swarm optimization-PSO), which allows finding a good solution to the problem of determining the priority (sequencing) of service or manufacturing of jobs scheduling of Flow Shop production systems. The combinatorial nature and complexity of the problem motivates the exploration of other alternative solutions to those traditionally used. Previously defined the ob-jective functions to optimize and the size of the swarm, the position and velocity of the particles are initialized. The objective function is then calculated and the best individual and global positions in the swarm are determined. Finally, speed and position are updated, repeating this procedure according to the number of iter-ations proposed. The algorithm is developed in Microsoft (R) Excel (R) and (R) Matlab, achieving better results than those obtained with other methods, such as the ser-vice factor, which increases by 19.9% for one machine and 20% for two machines.