基于改进PSO的装备维修任务调度方法

Research on Equipment Maintenance Task Scheduling Method Based on Improved PSO

针对现有装备维修任务调度方法存在维修时间过长、维修成本过高的问题,提出了基于改进粒子群算法(Particle Swarm Optimization,PSO)的装备维修任务调度方法。建立了以装备重要程度、维修时间、维修成本为指标的装备维修任务调度模型;从惯性权重、学习因子两个方面,提出了基于改进粒子群算法的装备维修任务调度模型求解方法;设计了算法仿真实例,仿真结果表明,该算法具有更快的收敛速度及更好的全局寻优能力,降低了维修时间,节约了维修成本,有效提高了装备维修任务调度的合理性。

In view of such shortcomings as the long maintenance time and high maintennance cost existed in equipment maintenance task scheduling methods,an improved particle swarm optimization(PSO)-based equipment maintenance task scheduling method is proposed.First,an equipment maintenance task scheduling model is established with the importance of equipment,maintenance time,and maintenance costs as indicators.Second,from the two aspects of inertia weights and learning factors,a solution method for the equipment maintenance task scheduling model based on improved particle swarm optimization is proposed.Finally,an algorithm simulation example is designed.The simulation results show that the algorithm has faster convergence speed and better global optimization capabilities,and it can reduce maintenance time,and can save maintenance costs,and can effectively improve the rationality of equipment maintenance task scheduling.