基于遗传算法和蒙特卡洛仿真的保障资源优化配置方法∗

摘要

保障资源的配置与维修组织的维修能力、人员编制和备件仓库储存空间密切相关，在满足约束条件的前提下如何合理地进行资源配置是完成装备可用度指标和降低保障费用的关键。针对该问题，在两级保障机构的背景下，对部件寿命和维修时间服从任意分布的复杂装备系统进行研究，采用遗传算法和蒙特卡洛仿真相结合的方法，建立了以保障费用为优化目标，使用可用度、仓库库存容量、维修人员编制等多约束条件下的保障资源配置优化模型。最后结合算例，对模型的适用性和方法的可行性进行了验证。%The configuration program of support resources is closely related to the maintenance capability of maintenance or⁃ganizations, staff limits and the reserve space of storehouses. How to deploy resources legitimately under the multi⁃constraints targets is the key to reach the equipment availability index as well as reduce life cycle cost ( LCC ) . In order to solve this problem, in the context of two levels support organization, the complicated equipments is selected in which the components’ life and repair time is subject to different life distributions as research objects, under the multi⁃targets constraint, such as e⁃quipment availability, storehouse volume and maintenance stuff limits, optimization method of resources configuration is es⁃tablished based on genetic algorithm( GA) and Monte Carlo simulation for the optimization goal of LCC. With the given ex⁃ample, the calculation results and the optimization process is analyzed to validate the applicability of the model and the effec⁃tiveness of the method.