工业工程 ›› 2023, Vol. 26 ›› Issue (6): 119-128.doi: 10.3969/j.issn.1007-7375.2023.06.013

• 系统建模与优化算法 • 上一篇    下一篇

基于改进被囊群算法的云制造分包服务组合研究

唐天兵, 陈永发, 蒙祖强   

  1. 广西大学 计算机与电子信息学院,广西 南宁 530004
  • 收稿日期:2022-10-20 发布日期:2024-01-09
  • 作者简介:唐天兵(1972-),男,四川省人,副教授,硕士,主要研究方向为优化算法、并行分布式计算、管理信息系统
  • 基金资助:
    国家自然科学基金资助项目 (62266004)

Cloud Manufacturing Subcontracting Service Composition Based on an Improved Tunicate Swarm Algorithm

TANG Tianbing, CHEN Yongfa, MENG Zuqiang   

  1. School of Computer Electronics and Information, Guangxi University, Nanning 530004, China
  • Received:2022-10-20 Published:2024-01-09

摘要: 针对云环境中制造任务数量庞大和分解复杂导致的制造周期长、成本高等问题,提出云制造分包服务组合方法。该方法是将任务分解为多个可并行执行的子任务,引入更多制造资源,提高市场竞争性,从而降低生产周期和成本。为高效求解云制造分包服务组合优化模型,对被囊群算法进行改进。首先共享种群个体信息,执行群体行为时融合周边个体位置,提高算法局部开发能力;其次共享个体历史信息,个体向同伴历史最优位置探索,提高算法全局开拓能力;最后根据当前搜索状态,种群自适应地调节全局开拓与局部开发行为,提高算法稳定性。通过仿真实验,证明所提方案对大规模制造任务的时间和成本控制优于对比方案。

关键词: 云制造, 分包, 服务组合, 被囊群算法

Abstract: To address the problems of long manufacturing cycles and high cost caused by the large number and complex decomposition of manufacturing tasks in a cloud environment, a composition method of cloud manufacturing subcontracting services is proposed. The method decomposes tasks into multiple sub-tasks that can be executed in parallel, and reduces production cycles and cost by introducing more manufacturing resources and improving market competitiveness. In order to efficiently solve the optimization model of cloud manufacturing subcontracting service composition, an improved tunicate swarm algorithm is proposed. First, the current information of individuals is shared, and the locations of surrounding individuals are integrated when performing group behavior, so as to improve the local exploitation ability of the algorithm; second, individual historical information is shared, and individuals explore the historical optimal location of others to improve the global exploration ability of the algorithm; finally, the global exploration and local exploitation behavior of the population is adjusted adaptively according to the current state to improve the stability of the algorithm. Through simulation experiments, it is verified that the proposed scheme is superior to the comparative one in controlling the time and cost of large-scale manufacturing tasks.

Key words: cloud manufacturing, subcontract, service composition, tunicate swarm algorithm (TSA)

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