面向大规模并发制造服务请求的资源优化配置
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摘要
针对如何高效处理云制造服务平台中大规模时序并发的制造服务请求这一问题,提出了一种面向服务响应时间的制造服务请求分段算法,通过制造任务相似性距离算法来保障分段算法的准确性。在分段算法保证制造服务请求完整性的前提下,构建了制造服务资源的关联区域。在此基础上,进一步提出了一种基于关联区域的制造服务资源分配算法,在时间维度上,保障了制造服务资源提供的公平性,从而提高了资源受限情况下的制造服务资源全局优化配置效率。最后通过实验测试和分析证明了算法的正确性和有效性。
Aiming at how to efficiently handle the massive temporal sequential manufacturing service request in cloud manufacturing service platform, this paper proposes a service response time-oriented service request segmentation algorithm. The manufacturing task similarity distance algorithm is used to guarantee the segmentation algorithm accuracy. Then the correlated region is constructed under the premise of ensuring the integrity of manufacturing service request. On the basis of this,a manufacturing service resources allocation algorithm based on correlated region is proposed so as to ensure the equal distribution of manufacturing service resources in temporal dimensions,and then to improve the efficiency of the global optimization of the manufacturing service resources in the case of limited resources. Finally,the correctness and validity of the algorithm are proved by experiment and analysis.
Aiming at how to efficiently handle the massive temporal sequential manufacturing service request in cloud manufacturing service platform, this paper proposes a service response time-oriented service request segmentation algorithm. The manufacturing task similarity distance algorithm is used to guarantee the segmentation algorithm accuracy. Then the correlated region is constructed under the premise of ensuring the integrity of manufacturing service request. On the basis of this,a manufacturing service resources allocation algorithm based on correlated region is proposed so as to ensure the equal distribution of manufacturing service resources in temporal dimensions,and then to improve the efficiency of the global optimization of the manufacturing service resources in the case of limited resources. Finally,the correctness and validity of the algorithm are proved by experiment and analysis.
引文
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[14]王国新,杜景军,阎艳,等.面向加工功能均衡分布的制造系统构形优化[J].计算机集成制造系统,2015,21(6):1497.
[15]贺可太,朱道云.云制造服务质量评价研究[J].计算机集成制造系统,2017.
[16]ZHANG Hongguo,HE Linyan,MA Chao,et al.Improved MultiRules-Based ACO algorithm for FJSS Problem in Cloud Manufacturing Environment[J].International Journal of Hybrid Information Technology 2016:29.
[17]张宏国,宫雪.Job-shop调度求解的广义蚁群算法[J].哈尔滨理工大学学报,2017,22(1):91.
[18]刘胜辉,李小阳,张淑丽.求解车间调度问题的双禁忌表禁忌搜索算法[J].哈尔滨理工大学学报,2016,21(6):50.
[19]乔佩利,马丽丽,郑林.基于改进粒子群算法的车间作业调度问题研究[J].哈尔滨理工大学学报,2011,16(2):35.
[2]SCHULTE S,HOENISCH P,HOCHREINER C,et al.Towards Process Support for Cloud Manufacturing[C]//IEEE International Conference on Enterprise Distributed Object Computing.2014:142.
[3]李伯虎,张霖,王时龙,等.云制造-面向服务的网络化制造新模式[J].计算机集成制造系统,2010,16(1):1.
[4]任磊,张霖,张雅彬,等.云制造资源虚拟化研究[J].计算机集成制造系统,2011,17(3):511.
[5]万曹雷,邵俊鹏.云制造环境下车间制造资源网格管理设计[J].哈尔滨理工大学学报,2013,18(5):37.
[6]LARTIGAU J,NIE L,XU X,et al.Scheduling Methodology for Production Services in Cloud Manufacturing[C]//International Joint Conference on Service Sciences.IEEE Computer Society,2012:34.
[7]王时龙,宋文艳,康玲,等.云制造环境下的制造资源优化配置研究[J].计算机集成制造系统,2012,18(7):1396.
[8]苏凯凯,徐文胜,李建勇.云制造环境下基于双层规划的资源优化配置方法[J].计算机集成制造系统,2015,21(7):1941.
[9]尹超,张云,钟婷.面向新产品开发的云制造服务资源组合优选模型[J].计算机集成制造系统,2012,18(7):1368.
[10]张淑丽,刘胜辉,沙晨明.求解柔性作业车间调度的岛屿模型遗传算法[J].哈尔滨理工大学学报,2016,21(5):101.
[11]胡艳娟,武理哲,张霖,等.云制造服务评价理论与方法研究综述[J].计算机集成制造系统,2017,23(3).
[12]易树平,谭明智,郭宗林,等.云制造服务平台中的制造任务分解模式优化[J].计算机集成制造系统,2015,21(8):2201.
[13]刘明周,王强,凌琳.基于分层任务网络的云制造任务分解方法[J].中国机械工程,2017,28(8):924.
[14]王国新,杜景军,阎艳,等.面向加工功能均衡分布的制造系统构形优化[J].计算机集成制造系统,2015,21(6):1497.
[15]贺可太,朱道云.云制造服务质量评价研究[J].计算机集成制造系统,2017.
[16]ZHANG Hongguo,HE Linyan,MA Chao,et al.Improved MultiRules-Based ACO algorithm for FJSS Problem in Cloud Manufacturing Environment[J].International Journal of Hybrid Information Technology 2016:29.
[17]张宏国,宫雪.Job-shop调度求解的广义蚁群算法[J].哈尔滨理工大学学报,2017,22(1):91.
[18]刘胜辉,李小阳,张淑丽.求解车间调度问题的双禁忌表禁忌搜索算法[J].哈尔滨理工大学学报,2016,21(6):50.
[19]乔佩利,马丽丽,郑林.基于改进粒子群算法的车间作业调度问题研究[J].哈尔滨理工大学学报,2011,16(2):35.