10.3778/j.issn.1673-9418.1509093
改进交互式蚁群算法及其应用
交互式蚁群优化(interactive ant colony optimization,iACO)是一种利用人来评价解的优劣而进行系统优化的技术,可以求解性能指标不能或者难以数量化的优化问题.分析了交互式蚁群优化模型面临的研究困难.针对Tanabe等人提出的交互式蚂蚁算法性能不足的问题,提出利用全局历史最优解进行信息素的更新,并将信息素限定在一定区间内的改进交互式蚁群优化算法,从人机交互角度讨论了解的构造方法和人的评价策略.最后,利用函数优化和汽车造型设计进行了实验,运行结果表明算法具有较高优化性能.
交互式蚁群优化、蚁群优化、人机交互、汽车造型
10
TP18(自动化基础理论)
The National Natural Science Foundation of China under Grant Nos.71271072,71331002;the Postdoctoral Science Foundation of China under Grant No.2014M560508;the Fundamental Research Funds for the Central Universities of China under Grant No.2013HGBH0029;the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20110111110006;the Natural Science Foundation of Anhui Province under Grant No.1208085MG121;the Research Foundation of Educational Commission of Anhui Province under Grant Nos.KJ2012A269,SK2015A537;the Scientific Research Foundation of Tongling University under Grant No.2014tlxyxs31
2017-02-24（万方平台首次上网日期，不代表论文的发表时间）
共9页
1720-1728
