Ant colony optimization on reliability optimization of redundancy allocation problem

doi:10.3778/j.issn.1002-8331.2009.15.019

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (15): 64-66.DOI: 10.3778/j.issn.1002-8331.2009.15.019

• 研究、探讨 • Previous Articles Next Articles

Ant colony optimization on reliability optimization of redundancy allocation problem

CHENG Shi-juan^1,2,LU Wei³,HE Ping²

1.Department of Applied Mechanics and Engineering，Southwest Jiaotong University，Chengdu 610031，China
2.Department of Applied Mathematics，Southwest Jiaotong University，Chengdu 610031，China
3.College of Computer and Mathematics，Xihua University，Chengdu 610039，China

Received:2008-06-24 Revised:2008-09-16 Online:2009-05-21 Published:2009-05-21
Contact: CHENG Shi-juan

蚁群算法在冗余系统可靠性最优分配上的应用

程世娟^1,2,卢伟³,何平²

1.西南交通大学应用力学与工程系，成都 610031
2.西南交通大学应用数学系，成都 610031
3.西华大学数学与计算机学院，成都 610039

通讯作者: 程世娟

Abstract

Abstract: Many heuristic algorithms had some flaws such as early convergence and easily falling in local peak.A ant colony optimization with identical state transition rules and pheromone updating rule is used to solve this problem.The experiment data showed that the ant colony optimization is an effective way to solve the redundancy allocation problem，which found the optimal solution in a relative short time.

Key words: ant colony optimization, Redundancy Allocation Problem（RAP）, state transition rule, pheromone update rule

摘要： 针对各种进化算法所存在的早熟收敛，易陷人局部极值点的缺点，采用两种不同的状态转移规则和与系统属性紧密相关的信息素更新规则，用蚁群算法解决元件可选择不同类型的最优冗余分配问题，实例仿真结果表明蚁群算法可以在相对短的时间内较快的找到问题的最优解。

关键词: 蚁群算法, 冗余系统分配问题, 状态转移规则, 信息素更新规则

CHENG Shi-juan^1,2,LU Wei³,HE Ping². Ant colony optimization on reliability optimization of redundancy allocation problem[J]. Computer Engineering and Applications, 2009, 45(15): 64-66.

程世娟^1,2,卢伟³,何平². 蚁群算法在冗余系统可靠性最优分配上的应用[J]. 计算机工程与应用, 2009, 45(15): 64-66.

[1]	ZHU Jiaying, GAO Maoting. AUV Path Planning Based on Particle Swarm Optimization and Improved Ant Colony Optimization [J]. Computer Engineering and Applications, 2021, 57(6): 267-273.
[2]	LI Zhuangkuo, CHANG Kaixuan. Ant Colony Optimization for Continuous Domains Applied to Cooperative Game [J]. Computer Engineering and Applications, 2021, 57(24): 198-204.
[3]	HE Yaying, FAN Xinwei. Application of Improved Ant Colony Optimization in Robot Path Planning [J]. Computer Engineering and Applications, 2021, 57(16): 276-282.
[4]	ZHANG Ming, DENG Wenhan, LIN Juan, ZHONG Yiwen. Modified Ant Colony Optimization Algorithm for Discounted {0-1} Knapsack Problem [J]. Computer Engineering and Applications, 2021, 57(13): 85-95.
[5]	HU Chunyang, JIANG Ping, ZHOU Genrong. Application of Improved Ant Colony Optimization in AGV Path Planning [J]. Computer Engineering and Applications, 2020, 56(8): 270-278.
[6]	ZHANG Hainan, YOU Xiaoming, LIU Sheng, LIU Zhongqiang. Interactive Learning Cuckoo Search Algorithm [J]. Computer Engineering and Applications, 2020, 56(7): 147-154.
[7]	FENG Jie, SHI Li. Research on Vehicle Routing Problem of Fresh Products with Pure Electric Refrigerator Truck [J]. Computer Engineering and Applications, 2019, 55(9): 237-242.
[8]	GAO Ling1，2, WANG Fan1, GAO Ni1，3, MAO Yong1. Security Hardening Measures Selection Model Based on Improved Ant Colony Optimization [J]. Computer Engineering and Applications, 2019, 55(7): 100-107.
[9]	XUE Wenyan, ZHAO Jiang, HAO Chongqing, LIU Huixian. Hyper Heuristic Ant Colony Optimization Algorithm Based on Pheromone Negative Feedback [J]. Computer Engineering and Applications, 2019, 55(4): 163-172.
[10]	JIANG Daoyin1，2, GE Hongwei1，2. Continuous Domain Ant Colony Optimization Algorithm Based on Information Exchange Strategy [J]. Computer Engineering and Applications, 2019, 55(11): 153-159.
[11]	ZHANG Jingyu, TENG Jianfu, BAI Yu. Research on Levy-DNA-ACO algorithm for medical image edge detection [J]. Computer Engineering and Applications, 2018, 54(8): 14-20.
[12]	JIANG Daoyin1，2, GE Hongwei1，2, YUAN Luo1. Density dynamic partition hybrid ant colony optimization for continuous domains [J]. Computer Engineering and Applications, 2018, 54(7): 144-151.
[13]	KONG Lin1, ZHANG Guofu1，2, SU Zhaopin1，2, JIANG Jianguo1，2. Ambulance emergency rescue routing planning for improved ant colony algorithm [J]. Computer Engineering and Applications, 2018, 54(13): 153-159.
[14]	YANG Yujun, CHEN Ye. Hybrid ant colony optimization for flexible robotic manufacturing cell scheduling problem [J]. Computer Engineering and Applications, 2018, 54(13): 160-167.
[15]	WU Baosheng, GUO Yu, WANG Falin, SONG Qian. Research on path planning of cable harness based on improved ant colony optimization [J]. Computer Engineering and Applications, 2018, 54(10): 236-241.

Ant colony optimization on reliability optimization of redundancy allocation problem

蚁群算法在冗余系统可靠性最优分配上的应用

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics