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计算机系统应用英文版:2017,26(9):195-199
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求解虚拟企业资源结盟博弈的启发式群智能优化算法
(南京财经大学 信息工程学院, 南京 210023)
Heuristic Swarm Intelligent Optimization Algorithm for Coalitional Resources Games in Virtual Enterprises
(College of Information and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China)
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Received:January 02, 2017    
中文摘要: 通过对求解虚拟企业资源结盟博弈问题与求解经典SAT问题相似性的分析,提出了一种求解虚拟企业资源结盟博弈的启发式群智能优化算法.算法融合萤火虫优化算法与布谷鸟优化算法部分原理,并设计可行的交叉算子以及变异优化算子,能够修复不可行解并保持种群多样性.实验结果表明本文算法的迭代次数与搜索到的稳定联盟数成线性增长,较启发式遗传算法有着更好的爬山性能和搜索能力.
Abstract:A heuristic swarm intelligent optimization algorithm for coalitional resources games in virtual enterprises is proposed by comparing the similarity of coalitional resources games in virtual enterprises with the classic SAT problem. The algorithm fuses portions of the principles of Glowworm swarm optimization algorithm and Cuckoo Search optimization algorithm. It designs the feasible cross operator and the mutational operator, which can repair infeasible solution and maintain diversity. Experimental results indicate that the algorithm's iterations linearly increase with the stable coalitions ever found. Compared with the heuristic genetic algorithm, it performs better in hill-climbing performance and searching efficiency.
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基金项目:科技部科技支撑项目(BAH29F01);江苏省农业科技自主创新资金项目(CX(15)1051);国家自然科学基金(71372188)
引用文本:
崔莹.求解虚拟企业资源结盟博弈的启发式群智能优化算法.计算机系统应用,2017,26(9):195-199
CUI Ying.Heuristic Swarm Intelligent Optimization Algorithm for Coalitional Resources Games in Virtual Enterprises.COMPUTER SYSTEMS APPLICATIONS,2017,26(9):195-199