# [1]苏春,黄茁,许映秋.基于遗传算法和蒙特卡洛仿真的设备维修策略优化[J].东南大学学报(自然科学版),2006,36(6):941-945.[doi:10.3969/j.issn.1001-0505.2006.06.014] 　Su Chun,Huang Zhuo,Xu Yingqiu.Optimization of devices’ maintenance and repair policy based on genetic algorithm and Monte Carlo simulation[J].Journal of Southeast University (Natural Science Edition),2006,36(6):941-945.[doi:10.3969/j.issn.1001-0505.2006.06.014] 点击复制 基于遗传算法和蒙特卡洛仿真的设备维修策略优化() 分享到： var jiathis_config = { data_track_clickback: true };

36

2006年第6期

941-945

2006-11-20

## 文章信息/Info

Title:
Optimization of devices’ maintenance and repair policy based on genetic algorithm and Monte Carlo simulation

Author(s):
School of Mechanical Engineering, Southeast University, Nanjing 211189, China

Keywords:

TP391.9;TB114.3
DOI:
10.3969/j.issn.1001-0505.2006.06.014

Abstract:
The complicated devices in which the components’ life is subject to non-exponential distribution and maintenance is subject to non-Markov process are selected as research objects, the system availability and general maintenance cost is selected as objective function, and the preventive maintenance cycle is set as decision variable. Then the maintenance policy optimization is carried out based on genetic algorithm(GA)and Monte Carlo simulation. The optimum model of device maintenance process is established. The individual evolution search in GA is used for the optimization of repair policy. The method of judging the failure of way set and disabling the components’ failures are used to solve the problem of excess failure in simulation. By establishing simulation history record and preferentially eliminating the records with small fitness values the simulation efficiency and optimum results are improved. An example of compound hydraulic and mechanical transmission system is given to validate the effectiveness of the method.

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