摘要
针对云制造环境复杂性和制造任务的多属性信息特征,提出一种基于任务相关性分析的制造任务优化分解方法。首先,研究云制造环境下的任务分解模型,对云制造任务进行形式化描述,在将制造总任务初步分解为元任务的基础上,使用专家评价法对元任务的物流相关度和信息相关度进行评估,通过计算任务的信息-物流相关系数,构造任务间的综合相关度公式,得到元任务之间的综合相关度。然后,以最大化子任务内部耦合度和最小化子任务之间的关联度为目标,建立适应度函数,并采用模拟退火算法求解任务分解模型,得到最终的任务分解结果。最后,通过仿真实例分析,验证了应用该算法进行云制造环境下制造任务优化分解的有效性。
In this article,in view of the complexity of the cloud manufacturing environment and the multi-attribute information characteristics of the manufacturing tasks,a method for optimized decomposition of the manufacturing tasks based on the taskcorrelation analysis is proposed.Firstly,the model of task decomposition is set up in the cloud manufacturing environment.The task is subject to form description and divided into some meta tasks;then,the logistics correlation and information correlation of the meta tasks are evaluated with the help of the expert evaluation method.The formula of comprehensive correlation between the meta tasks is constructed by computing the logistics-information correlation coefficient of the manufacturing tasks.Secondly,in order to maximize the internal coupling degree and minimize the external correlation degree of the subtasks,the fitness function is set up,and the simulated annealing algorithm is used to solve the model of task decomposition;thus,the final results of task decomposition are identified.Finally,the simulation examples have verified that this algorithm is effective for optimized decomposition of the manufacturing tasks in the cloud manufacturing environment.
作者
付景枝
王继飞
马悦
刘云平
FU Jing-zhi;WANG Ji-fei;MA Yue;LIU Yun-ping(School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044;Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET),Nanjing 210044)
出处
《机械设计》
CSCD
北大核心
2023年第3期65-69,共5页
Journal of Machine Design
基金
国家自然科学基金资助项目(51305210)
江苏省自然基金项目(BK20150924)。
关键词
云制造
任务分解
物流相关度
信息相关度
模拟退火算法
cloud manufacturing
task decomposition
logistics correlation
information correlation
simulated annealing algorithm
