首页 | 本学科首页   官方微博 | 高级检索  
     

基于蚁群算法的试验流程优化研究
引用本文:陈慕齐 齐欢 陈迎春. 基于蚁群算法的试验流程优化研究[J]. 海军工程学院学报, 2006, 18(3): 38-42
作者姓名:陈慕齐 齐欢 陈迎春
作者单位:[1]华中科技大学管理学院,湖北武汉430074 [2]华中科技大学控制科学与工程系,湖北武汉430074
摘    要:水中兵器的海上试验涉及许多人员、兵力、被试产品、测量设备等,试验周期长、消耗大,因此如何缩短试验周期是亟待研究解决的问题.文中首先将试验流程优化问题转化为车间调度问题,建立了相应的数学模型,再应用蚁群算法转移规则得到中间结果并进行排队以对各种资源约束进行处理.最后将结果利用局部搜索算法优化后作为蚁群算法信息素更新的基础.实例计算结果表明,该方法优化效果良好.

关 键 词:蚁群算法 车间调度问题 水中兵器
文章编号:1009-3486(2006)03-0038-05
收稿时间:2005-10-18
修稿时间:2006-03-10

Test scheduling based on ant colony optimization
CHEN Mu-qi, QI Huan, CHEN Ying-chun. Test scheduling based on ant colony optimization[J]. , 2006, 18(3): 38-42
Authors:CHEN Mu-qi   QI Huan   CHEN Ying-chun
Abstract:With regard to much manpower, forces, under-proof products and measurement equipment, the sea tests for underwater weapons will take a long period and great expenditure. Therefore, the test scheduling is what needs to be dealt with. The test scheduling is first converted into a job shop scheduling problem. The corresponding mathematical model is established. Then the transition rules of ant colony algorithm are adopted to obtain intermediate result before the queuing theory is used to deal with different resource constraints. Finally, a local search method is used for further optimization before the pheromones of ants are updated. The simulation results prove the validity of the algorithm.
Keywords:ant colony optimization   job shop scheduling problem   underwater weapon
本文献已被 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号