[1]常瑞云[],周井泉[],许斌[],等. 基于离散人工群算法的云制造服务组合[J].计算机技术与发展,2016,26(07):177-182.
　CHANG Rui-yun[],ZHOU Jing-quan[],XU Bin[],et al. Could Computing Service Composition Based on Discrete Artificial Bee Colony Algorithm[J].,2016,26(07):177-182.
点击复制

 基于离散人工群算法的云制造服务组合()
分享到：

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

卷:
26
期数:
2016年07期
页码:
177-182
栏目:
应用开发研究
出版日期:
2016-07-10

文章信息/Info

Title:
 Could Computing Service Composition Based on Discrete Artificial Bee Colony Algorithm
文章编号:
1673-629X（2016)07-0177-06
作者:
 常瑞云[1]; 周井泉[1]; 许斌[2]; 亓晋[2]
 1.南京邮电大学 电子科学与工程学院；2.南京邮电大学 物联网学院
Author(s):
 CHANG Rui-yun[1] ; ZHOU Jing-quan[1]; XU Bin[2]; QI Jin[2]
关键词:
 ; 云制造服务组合; ABC算法; LSDABC算法; QoS; 局部搜索
Keywords:
 ; cloud manufacturing service composition; ABC; LSDABC; QoS; location search
分类号:
TP301.6
文献标志码:
A
摘要:
 随着互联网、云计算等网络技术的快速发展,单一制造服务已无法满足用户日益复杂的制造任务,所以云制造服务组合问题一直是近年来应用和研究的热点,为典型NP难题。文中针对云制造服务组合优选问题,改进原始人工蜂群算法( Artificial Bee Colony,ABC),提出了一种基于局部搜索离散蜂群算法( Location Search Discrete Artificial Bee Colony,LSD-ABC),从而为用户选择服务质量( Quality of Service,QoS)最优的服务组合执行路径。该算法引入种群的选择概率和对最优解的局部搜索策略,提升算法的开采能力、收敛速度,同时避免出现搜索停滞陷入局部最优。最后将LSDABC应用于云制造服务组合优选中进行仿真实验,并将结果与原始ABC、DE、PSO算法进行对比。实验结果表明,LSDABC具有较好的求解质量和鲁棒性。
Abstract:
 With the rapid development of network technology such as Internet,cloud computing and so on,single manufacturing service has already not satisfied the increasingly complex tasks for users. So,cloud manufacturing service composition,as a NP hard problem,has been the applied and research hotspot in recent years. As to service composition optimal selection,a Location Search Discrete Artificial Bee Colony ( LSDABC) is proposed in this paper based on improvement of original ABC to provide the service composition execution path with optimal QoS for users. This algorithm introduces selection probability based on population and local search strategy to improve the exploitation ability and convergence speed and to avoid falling into local optimum. Finally,LSDABC is applied to the cloud manufac-turing service composition. The experiment shows that the LSDABC has better quality and robustness compared with the original ABC, DE and PSO.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(07):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(07):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(07):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(07):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(07):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(07):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(07):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
　SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(07):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
　YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(07):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
　YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(07):47.

更新日期/Last Update: 2016-09-28