HPSO in the application of the equipment maintenance task scheduling

The task scheduling of military equipment maintenance plays an increasingly vital role, however, the traditional scheduling algorithms lack environmental adaptability, and the optimizing process is uncontrollable. Therefore, combined with the genetic algorithm, an improved hybrid particle swarm optimization (HPSO) model is built. Based on the mathematical description of this problem, the discretization is conducted to simplify the domain of variables, and the concentration monitoring mechanism is introduced to integrate the particle's concentration distribution and fitness information, so as to control the particles' evolution. By defining the spatial fitness, the crossover operation and mutation operation are used to speed up the evolution and prevent the local optimization. Analyzing the results of instance, it indicates the excellent performance of HPSO algorithm in terms of the convergence speed and accuracy.