基于协同效应的并行制造云服务组合算法
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摘要
为了解决并行结构下制造云服务的组合优化问题,从协同效应的角度提出一种基于反向和局部学习的蚁群算法。该算法以服务质量作为信息素构建协同效应评价模型,求解并行服务的协同效应值,作为启发函数参数。利用协同关系矩阵计算组合协同效应值,并将其与组合服务质量相结合,求解综合评价值最高的服务组合。实验结果表明,该算法能有效求解并行制造云服务的组合优化问题,并能较快地得到最优解。
To solve the problem of manufacturing cloud service composition optimization in parallel structure,an improved ant colony algorithm based on reverse-learning and local-learning was proposed from the perspective of collaborative effect.An evaluation model was established to calculate the value of collaborative effect as the heuristic function parameter,and the quality of service as the pheromone.Then,the collaborative effect of service composition calculated by collaborative relationship matrix was combined with the quality of service composition to obtain the optimal service composition.The experimental results showed that the improved algorithm was effective and feasible,which could achieve the global optimal solution quickly.
To solve the problem of manufacturing cloud service composition optimization in parallel structure,an improved ant colony algorithm based on reverse-learning and local-learning was proposed from the perspective of collaborative effect.An evaluation model was established to calculate the value of collaborative effect as the heuristic function parameter,and the quality of service as the pheromone.Then,the collaborative effect of service composition calculated by collaborative relationship matrix was combined with the quality of service composition to obtain the optimal service composition.The experimental results showed that the improved algorithm was effective and feasible,which could achieve the global optimal solution quickly.
引文
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[19]XIA Xuewen,LIU Jingnan,GAO Kefu,et al.Particle swarm optimization algorithm with reverse-learning and local-learning behavior[J].Chinese Journal of Computers,2015,38(7):1397-1407(in Chinese).[夏学文,刘经南,高柯夫,等.具备反向学习和局部学习能力的粒子群算法[J].计算机学报,2015,38(7):1397-1407.]
[2]LI Bohu,ZHANG Lin,REN Lei,et al.Further discussion cloud manufacturing[J].Computer Integrated Manufacturing Systems,2010,17(3):449-457(in Chinese).[李伯虎,张霖,任磊,等.再论云制造[J].计算机集成制造系统,2011,17(3):449-457.]
[3]YIN Chao,HUANG Biqing,LIU Fei,et al.Common key technology system of cloud manufacturing service platform for small and medium enterprises[J].Computer Integrated Manufacturing Systems,2011,17(3):495-503(in Chinese).[尹超,黄必清,刘飞,等.中小企业云制造服务平台共性关键技术体系[J].计算机集成制造系统,2011,17(3):495-503.]
[4]ZHANG Lin,LUO Yongliang,TAO Fei,et al.Study on the key technologies for the construction of manufacturing cloud[J].Computer Integrated Manufacturing Systems,2010,16(11):2510-2520(in Chinese).[张霖,罗永亮,陶飞,等.制造云构建关键技术研究[J].计算机集成制造系统,2010,16(11):2510-2520.]
[5]TAO Fei,ZHANG Lin,GUO Hua,et al.Typical characteristics of cloud manufacturing and several key issues of cloud service composition[J].Computer Integrated Manufacturing Systems,2011,17(3):477-486(in Chinese).[陶飞,张霖,郭华,等.云制造特征及云服务组合关键问题研究[J].计算机集成制造系统,2011,17(3):477-486.]
[6]LIU Z Z,CHU D H,SONG C,et al.Social learning optimization algorithm paradigm and its application in QoS-aware cloud service composition[J].Information Sciences,2016,326(C):315-333.
[7]STRUNK A.QoS-aware service composition:a survey[C]//Proceedings of the 8th IEEE European Conference on Web Service.Washington,D.C.,USA:IEEE,2010:67-74.
[8]XUE X,WANG S,LU B.Manufacturing service composition method based on networked collaboration mode[J].Journal of Network and Computer Applications,2016,59(C):28-38.
[9]DONG Yuanfa,GUO Gang.Evalution and selection approach for cloud manufacturing service based on template and global trust degree[J].Computer Integrated Manufacturing Systems,2014,20(1):207-214(in Chinese).[董元发,郭刚.基于模板与全局信任度的云制造服务评价与选择方法[J].计算机集成制造系统,2014,20(1):207-214.]
[10]TAI Lijun,HU Rufu,ZHAO Han,et al.Multi-objective dynamic scheduling of manufacturing resource to cloud manufacturing services[J].China Mechanical Engineering,2013,24(12):1616-1622(in Chinese).[邰丽君,胡如夫,赵韩,等.面向云制造服务的制造资源多目标动态优化调度[J].中国机械工程,2013,24(12):1616-1622.]
[11]WEI Le,ZHAO Qiuyun,SHU Hongping.Adaptive adjustment of composite cloud service based on QoS for cloud manufacturing environment[J].Journal of Lanzhou University:Nature Sciences,2012,48(4):98-104(in Chinese).[魏乐,赵秋云,舒红平.云制造环境下基于QoS的组合云服务自适应调整[J].兰州大学学报:自然科学版,2012,48(4):98-104.]
[12]XIANG Feng.Research on key techniques of energy consumption aware service composition in cloud manufacturing system[D].Wuhan:Wuhan University of Technology,2013(in Chinese).[向峰.云制造系统中基于能耗的服务组合关键技术研究[D].武汉:武汉理工大学,2013.]
[13]JING Shikai,JIANG Hao,XU Wenting,et al.Cloud manufacturing service composition considering execution reliability[J].Journal of Computer-Aided Design&Computer Graphics,2014,26(3):392-400(in Chinese).[敬石开,姜浩,许文婷,等.考虑执行可靠性的云制造服务组合算法[J].计算机辅助设计与图形学学报,2014,26(3):392-400.]
[14]MA Wenlong,WANG Zheng,ZHAO Yanwei.Optimizing services composition in cloud manufacturing based on improved ant colony algorithm[J].Computer Integrated Manufacturing Systems,2016,22(1):113-121(in Chinese).[马文龙,王铮,赵燕伟.基于改进蚁群算法的制造云服务组合优化[J].计算机集成制造系统,2016,22(1):113-121.]
[15]XIA Yamei,CHENG Bo,CHEN Junliang,et al.Optimizing services composition based on improved ant colony algorithm[J].Chinese Journal of Computers,2012,35(2):2270-2281(in Chinese).[夏亚梅,程渤,陈俊亮,等.基于改进蚁群算法的服务组合优化[J].计算机学报,2012,35(2):2270-2281.]
[16]LI Jing,ZHANG Yongan.An analysis of the affecting factors of collaborative effect of the logistics networks:a case study of SUNING's core logistics networks[J].Journal of Beijing Jiaotong University:Social Sciences Edition,2011,10(4):45-52(in Chinese).[李靖,张永安.基于ISM的物流网络协同效应影响因素分析---以苏宁电器为核心的物流网络为例[J].北京交通大学学报:社会科学版,2011,10(4):45-52.]
[17]FENG Bo,FAN Zhiping.A partner selection method for knowledge creation team based on collaborative effect[J].Chinese Journal of Management,2012,9(2):258-261(in Chinese).[冯博,樊治平.基于协同效应的知识创新团队伙伴选择方法[J].管理学报,2012,9(2):258-261.]
[18]MA Wenlong,ZHU Linan,WANG Wanliang.Cloud service selection model based on QoS-aware in cloud manufacturing environment[J].Computer Integrated Manufacturing Systems,2014,20(5):1246-1254(in Chinese).[马文龙,朱李南,王万良.云制造环境下基于QoS感知的云服务选择模型[J].计算机制造系统,2014,20(5):1246-1254.]
[19]XIA Xuewen,LIU Jingnan,GAO Kefu,et al.Particle swarm optimization algorithm with reverse-learning and local-learning behavior[J].Chinese Journal of Computers,2015,38(7):1397-1407(in Chinese).[夏学文,刘经南,高柯夫,等.具备反向学习和局部学习能力的粒子群算法[J].计算机学报,2015,38(7):1397-1407.]
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