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Application of Improved Particle Swarm Optimization in Vehicle Depot Overhaul Shop Scheduling

This paper improves the particle swarm optimization algorithm by eliminating the velocity term of particles and adjusting the weight value in a linear decreasing way, and gives an update factor variable, which has a minimum probability to update the positions of all particles randomly, thus increasing the global search ability, obtaining a better maintenance time, and then discharging the optimal scheduling scheme. Finally, the simulation experiment of the model and the improved algorithm is carried out by using part of the repair data of a vehicle depot, which verifies the superiority and effectiveness of the improved particle swarm optimization algorithm.