复杂系统的选择性维修模型和求解算法

Selective maintenance model and its solving algorithm for complex system

考虑不修、最小维修、换件维修和多中间维修水平,提出了一种基于粒子群优化(PSO)算法和多员维修的复杂系统选择性维修模型,将组件维修前状态、组件有效役龄和维修费用等因素引入不完全维修模型,更符合工程实际。提出了一种基于多员维修的系统组件维修分配算法,解决了如何将多维修任务分配给多维修人员,使得系统维修时间最小的问题,并将所提算法引入到PSO算法中,求解考虑多维修人员和不完全维修条件的复杂系统选择性维修模型。案例表明:所提模型和求解算法有效,能够为复杂系统提供切实有效的维修决策方案。

Considering no maintenance, minimal maintenance, replacement maintenance and multiple intermediate maintenance levels, a selective maintenance model for the complex system is proposed based on Particle Swarm Optimization(PSO) algorithm and multiple repairpersons. In the imperfect maintenance model, effective age, maintenance cost and pre-maintenance state of components are introduced, which is more in line with the engineering practice. A system components maintenance tasks assignment algorithm, to solve the problem of how to assign multiple maintenance tasks to multiple repairpersons in order to minimize the maintenance time, is also proposed. Furthermore, the proposed algorithm is introduced into the PSO algorithm to solve the selective maintenance model, which is given for complex system considering multiple repairpersons and imperfect maintenance. The results of case analysis show that the proposed model and the corresponding algorithm are effective, and can provide feasible maintenance decision-making schemes for complex system.