摘要
云制造组合优化中对于服务资源历史执行情况考虑不足时会使得服务资源执行能力是否可信具有不确定性,最终可能影响任务成功执行,为解决该问题建立了一种考虑执行能力的云制造服务资源组合优化模型。该模型针对服务资源历史执行情况信息的时效性,建立时间段权重衰减函数,以成本、时间、合格率、可靠性、可维护性为决策目标,运用改进的带有外部归档的自适应差分进化算法(JADE)求解。实验结果证明,该模型能够有效解决考虑执行能力的云制造组合优化问题,改进的JADE算法相比原算法收敛性更好。
Insufficient consideration of the historical execution of service resources in cloud manufacturing portfolio optimization will lead to uncertainty about whether the execution ability of service resources is credible,which will affect the successful execution of tasks.In order to solve this problem,this study established a cloud manufacturing service resource composition optimization model considering the execution capacity.Aiming at the timeliness of the historical execution information of service resources,the model established a time period weight attenuation function.Then the model took cost,time,pass rate,reliability and maintainability as its decision goals and solved the model by an improved adaptive differential evolution algorithm(JADE)with optional external archiving.Experimental results prove that this model can effectively solve the combinatorial optimization problem of cloud manufacturing considering the execution capability.Moreover,the improved JADE algorithm has better convergence than the original one.
作者
谢程龙
石宇强
XIE Chenglong;SHI Yuqiang(School of Manufacturing Science and Engineering,Southwest University of Science and Technology,Mianyang 621010,Sichuan,China)
出处
《西南科技大学学报》
CAS
2021年第2期55-61,共7页
Journal of Southwest University of Science and Technology
基金
四川省教育厅科研项目(18ZA0497)。
关键词
云制造
组合优化
JADE算法
Cloud manufacturing
Combination optimization
JADE algorithm
