文章摘要
王博朝,陈菊红,李彦锋,习大润,焦飞强,刘善慧.考虑资源需求差异的印包设备网络协同制造资源匹配方法[J].包装工程,2024,45(9):225-231.
WANG Bozhao,CHEN Juhong,LI Yanfeng,XI Darun,JIAO Feiqiang,LIU Shanhui.Resource Matching Method for Collaborative Manufacturing of Printing Package Equipment Network Considering Differences in Resource Demand[J].Packaging Engineering,2024,45(9):225-231.
考虑资源需求差异的印包设备网络协同制造资源匹配方法
Resource Matching Method for Collaborative Manufacturing of Printing Package Equipment Network Considering Differences in Resource Demand
投稿时间:2023-06-26  
DOI:10.19554/j.cnki.1001-3563.2024.09.029
中文关键词: 印包设备  协同制造  资源匹配  遗传算法  莱维飞行
英文关键词: printing package equipment  collaborative manufacturing  resource matching  genetic algorithm  levy flight
基金项目:国家重点研发计划(2019YFB1707201)
作者单位
王博朝 西安理工大学 经济与管理学院西安 710048 
陈菊红 西安理工大学 经济与管理学院西安 710048 
李彦锋 陕西北人印刷机械有限责任公司陕西 渭南 714000 
习大润 陕西北人印刷机械有限责任公司陕西 渭南 714000 
焦飞强 陕西北人印刷机械有限责任公司陕西 渭南 714000 
刘善慧 西安理工大学 包装印刷与数字媒体学院西安 710048 
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中文摘要:
      目的 包装印刷装备行业存在制造资源分散、产业协同不足和效率低等问题,针对网络协同制造中的制造资源匹配问题提出一种有效方法。方法 从不同子任务资源需求差异视角出发,构建基于TQCS制造资源评价指标体系及制造任务约束体系,通过层次分析法计算不同子任务的权重,以资源与任务的匹配度最大为目标函数,提出基于莱维飞行–遗传算法的网络协同制造资源匹配方法。结果 改进的资源匹配方法相较于传统方法,能够得到成本更低、时间更短的方案,并且改进的遗传算法的寻优能力更高。结论 相较于传统方法,改进的制造资源匹配方法的目标函数更合理、权重取值更客观、寻优能力更好,能够得到更为合理的制造资源匹配方案。
英文摘要:
      The work aims to provide an effective method for the matching of manufacturing resources in the collaborative manufacturing of packaging and printing equipment network to solve the problems of dispersed manufacturing resources, lack of industrial coordination and low efficiency. From the perspective of different subtask resource demand difference, a manufacturing resource evaluation index system and a manufacturing task constraint system was built based on TQCS to calculate the weight of different subtasks with resources and task maximum matching degree as the target function, to propose a matching method for network collaborative manufacturing resources based on the levy flight genetic algorithm. The improved resource matching method could get lower cost and shorter time than the traditional method, and the improved genetic algorithm has higher optimization ability than the traditional genetic algorithm. Compared with the traditional method, the manufacturing resource matching method proposed in this paper has more reasonable objective functions, more objective weight values and better optimization ability, and can get a more reasonable manufacturing resource matching scheme.
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