Parallel manufacturing cloud service composition algorithm based on collaborative effect

被引：0

作者：

Chen Y. ^{[1
]}

Liu J. ^{[1
]}

Ling L. ^{[1
]}

Wang L. ^{[1
]}

机构：

[1] State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2019年 / 25卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Ant colony algorithm; Cloud manufacturing; Collaborative effect; Parallel service composition; Quality of service;

D O I：

10.13196/j.cims.2019.01.013

中图分类号：

学科分类号：

摘要：

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. © 2019, Editorial Department of CIMS. All right reserved.

引用

页码：137 / 146

页数：9

共 19 条

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