Multi-objective Optimization Model and Adaptive Particle Swarm Algorithm for Complex Equipment Maintenance Support Intelligent Mission Planning

Aiming at the large-scale multi-objective and multi-constraint problem of equipment maintenance support, the process and content are analyzed, and a general model of multi-objective optimization is constructed. On this basis, mission priority based multi-objective optimization model and particle swarm optimization algorithm are proposed. Aiming at on-site emergency repair missions requirements, a multi-objective intelligent optimization decision-making model and multi-objective particle swarm implementation algorithm based on the fuzzy learning subgroups are put forward. The results of simulation experiments show that the optimization model and implementation algorithm for maintenance mission planning based on task prioritization has fast convergence compared to the traditional algorithm; Intelligent optimization model and multi-objective particle swarm implementation algorithm for on-site emergency repair operations can help the commander to select the optimal solution from a limited number of alternative optimization solutions. Finally, this paper proposes some countermeasures to improve the level of intelligent mission planning for equipment maintenance support.