[1]马登武 张勇亮 姚成柱 陈军青 王彦.基于蚁群算法的飞机定检原位工作流程优化[J].计算机技术与发展,2012,(01):147-151.
　MA Deng-wu,ZHANG Yong-liang,YAO Cheng-zhu,et al.Optimization of Plane＇s Primary Periodic Maintenance Workflow Based on Ant Colony Optimization[J].,2012,(01):147-151.
点击复制

基于蚁群算法的飞机定检原位工作流程优化()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年01期
页码:
147-151
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Optimization of Plane＇s Primary Periodic Maintenance Workflow Based on Ant Colony Optimization
文章编号:
1673-629X（2012）01-0147-05
作者:
马登武1 张勇亮1 姚成柱1 陈军青2 王彦1
[1]海军航空工程学院[2]92154部队
Author(s):
MA Deng-wu ;  ZHANG Yong-liang ;  YAO Cheng-zhu ;  CHEN Jun-qing;  WANG Yan
[1]Naval Aeronautical and Astronautical University[2]Regiment 92154
关键词:
蚁群算法; 飞机定检; 原位工作; 流程优化模型
Keywords:
ACO ;  plane＇ s periodic maintenance ;  primary work;  workflow optimization model
分类号:
TP39
文献标志码:
A
摘要:
首次将蚁群算法（ACO）应用于飞机定检原位工作流程优化中。在建立原位工作流程优化模型的基础上，借鉴最优一最差蚂蚁系统的思想改进信息素更新机制，并采用改进的精英策略和变异特征对基本蚁群算法进行改进。实例仿真表明，改进蚁群算法在全局搜索能力和收敛速度上较基本蚁群算法有明显提高，克服了基本蚁群算法搜索时间长、容易早熟的不足。优化后原位工作完成时问较优化前缩短2．27％，验证了ACO在解决定检工作流程优化问题上的适用性
Abstract:
Ant Colony Optimization （ACO） is used to optimize plane＇ s periodic maintenance primary workflow firstly. After the model of primary work is built, the renew-tactics of the pheromone is improved according to the method of Best-Worst Ant System（ BWAS）, then improved elite selecting tactics and mutation characteristic are used to improve the simple ACO. The simulation results demonstrate that,the improved ACO is much stronger in global-best solution search ability and much quicker than the simple ACO, and overcomes the deficiency of being long in search and easy to ＂precocity＂ of the simple ACO. After optimization the finish time of primary work is shorter 2.27% than before, and proves that ACO is good for the optimization of primary periodic maintenance workflow

相似文献/References:

[1]段军,张清磊.蚁群算法在LEACH路由协议中的应用[J].计算机技术与发展,2014,24(01):65.
　DUAN Jun,ZHANG Qing-lei.Application of Ant Colony Algorithm Based on LEACH Routing Protocol[J].,2014,24(01):65.
[2]何小娜 逄焕利.基于二维直方图和改进蚁群聚类的图像分割[J].计算机技术与发展,2010,(03):128.
　HE Xiao-na,PANG Huan-li.Image Segmentation Based on Improved Ant Colony Clustering and Two- Dimensional Histogram[J].,2010,(01):128.
[3]熊伟平 曾碧卿.几种仿生优化算法的比较研究[J].计算机技术与发展,2010,(03):9.
　XIONG Wei-ping,ZENG Bi-qing.Studies on Some Bionic Optimization Algorithms[J].,2010,(01):9.
[4]宋世杰 刘高峰 周忠友 卢小亮.基于改进蚁群算法求解最短路径和TSP问题[J].计算机技术与发展,2010,(04):144.
　SONG Shi-jie,LIU Gao-feng,ZHOU Zhong-you,et al.An Improved Ant Colony Algorithm Solving the Shortest Path and TSP Problem[J].,2010,(01):144.
[5]林本强 唐依珠.基于蚁群算法的移动自适应网QoS路由算法[J].计算机技术与发展,2009,(06):9.
　LIN Ben-qiang,TANG Yi-zhu.Ant Colony Algorithm Based Ad Hoc Network QoS Routing Algorithm[J].,2009,(01):9.
[6]古明家 宣士斌 廉侃超 李永胜.基于蚁群和人工鱼群算法融合的QoS路由算法[J].计算机技术与发展,2009,(07):145.
　GU Ming-jia,XUAN Shi-bin,LIAN Kan-chao,et al.QoS Routing Algorithm Based on Combination of Modified Ant Colony Algorithm and Artificial Fish Swarm Algorithm[J].,2009,(01):145.
[7]贾瑞玉 张新建 冯伦阔 李永顺.信息素增量动态更新的改进蚁群算法[J].计算机技术与发展,2009,(09):32.
　JIA Rui-yu,ZHANG Xin-jian,FENG Lun-kuo,et al.Ant Colony Algorithm with Dynamic Pheromones Increment Updating[J].,2009,(01):32.
[8]鲍娜 张德贤 孙傲冰 王飞.基于改进蚁群算法的网格组合拍卖资源分配[J].计算机技术与发展,2009,(10):149.
　BAO Na,ZHANG De-xian,SUN Ao-bing,et al.Research on Resource Allocation of Combinatorial Auction in Grid Based on Improved Ant Colony Algorithm[J].,2009,(01):149.
[9]邓义乔 张代远.蚁群算法在搜索引擎系统中的应用研究[J].计算机技术与发展,2009,(12):21.
　DENG Yi-qiao,ZHANG Dai-yuan.Research and Application of Ant Colony Algorithm in Searching Engine System[J].,2009,(01):21.
[10]段凤玲 李龙澍 曹文婷.具有多态特征和聚类处理的蚁群算法[J].计算机技术与发展,2009,(12):77.
　DUAN Feng-ling,LI Long-shu,CAO Wen-ting.Ant Colony Algorithm with Polymorphism and Clustering Processing[J].,2009,(01):77.

备注/Memo

备注/Memo:
马登武（1964-），男，山东淄博人，教授，博导，博士，研究方向为航空武器系统运用工程；张勇亮（1986-），男，河北沧州人，硕士生，研究方向为系统工程与应用
更新日期/Last Update: 1900-01-01