计算机集成制造系统 ›› 2018, Vol. 24 ›› Issue (第4): 838-850.DOI: 10.13196/j.cims.2018.04.004

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基于混合任务网络的智慧制造任务协同分配模型

任磊,任明仑+   

  1. 合肥工业大学教育部过程优化与智能决策重点实验室
  • 出版日期:2018-04-30 发布日期:2018-04-30
  • 基金资助:
    国家自然科学基金重点资助项目(71531008,71271073)。

Task allocation model for wisdom manufacturing based on hybrid task network

  • Online:2018-04-30 Published:2018-04-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71531008,71271073).

摘要: 复杂任务场景下,由于制造子任务间存在多维的物料、信息、知识交互和传递关系,对匹配服务单元间的协同能力提出一致性要求,任务关系与服务协同关联匹配不精确将带来额外协调和交互成本,降低资源配置效率,而传统任务分配模型忽视任务关系约束对分配结果的影响。鉴于此,通过任务网络与服务协同网络的动态匹配,构建了面向任务关系约束的任务协同分配方法。针对“好钢未用在刀刃上”现象,综合用户偏好和网络中心性分配任务权重,提出基于权重的服务胜任度聚合方法;针对“1+1<2”不协同现象,提出基于横向协同和纵向协同的服务协同水平计算方法;综合考虑服务群体的胜任度和协同水平,提出基于混合任务网络的多目标任务分配优化数学模型。利用改进非支配粒子群算法进行求解得到Pareto最优解集,根据用户偏好和实际制造情形,通过加权TOPSIS评估获取个性化、灵活的最佳分配方案。运用汽车云制造仿真实验,验证了模型的有效性,通过在最好解、平均解和运行时间上与其他算法进行对比,分析了所提方法的优势。

关键词: 混合任务网络, 任务分配, 多目标优化, 加权TOPSIS

Abstract: For complex task,the collaboration ability between matching service units should be consistent,otherwise the collaborated cost would increase and the allocated efficiency would decrease.But the traditional task allocation model was difficult to meet the requirements of collaborative manufacturing.To solve this problem,the task allocation strategy and process were proposed by constructing multidimensional task graph.Aiming at the phenomenon that “Good steel is not used for the blade's edge”,a service competent aggregation method was built based on task weight,which integrated the user's preference and network centrality as index.In view of “1+1<2” non-synergy phenomenon,the service synergy level based on horizontal and vertical collaboration was put forward.By considering the competent and synergy level of service groups,a multi-objective optimization mathematical model was constructed,and the improved non-dominated particle swarm optimization algorithm was used to obtain Pareto optimal solution set.According to the user preferences and actual manufacturing situation,a personalized optimal scheme was acquired with weighted TOPSIS.The simulation experiment verified the validity of the model,and the advantages of this method were analyzed by comparing with other algorithms in the dimensions of best solution,average solution and running time.

Key words: hybrid task network, task allocation, multi-objective optimization, weighted TOPSIS

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