云制造平台下基于蝙蝠算法的供需调度时间优化

发布时间：2018-03-21 17:03

本文选题：云制造　切入点：供应链　出处：《现代情报》2014年10期 　论文类型：期刊论文

【摘要】：云制造平台为供应链构建提供了多种选择,为了解决云制造平台下,供应链调度数据量大,更新频繁的问题,对蝙蝠算法重新编码及解码,应用改进蝙蝠算法对初始种群的产生进行限定,解决批任务调度问题,减少无效搜索,缩短找到合适任务分派策略的时间,通过实验对比,证明了改进蝙蝠算法在云制造供应链调度中的有效性,避免了资源超载和资源闲置的现象,并使任务总完成时间最短,推动云制造在供应链方面的应用。
[Abstract]:Cloud manufacturing platform provides a variety of options for the construction of supply chain. In order to solve the problem of large amount of scheduling data and frequent updating of supply chain under cloud manufacturing platform, the bat algorithm is recoded and decoded. The improved bat algorithm is used to limit the initial population, solve the batch task scheduling problem, reduce the invalid search, shorten the time to find the appropriate task assignment strategy, and compare with the experiment. It is proved that the improved bat algorithm is effective in cloud manufacturing supply chain scheduling, avoids the phenomenon of resource overload and idle resources, and makes the total task completion time shortest, and promotes the application of cloud manufacturing in supply chain.
【作者单位】：上海理工大学管理学院;
【基金】：国家自然科学基金资助项目“行为驱动、学习效应嵌入的TFT-LCD调度建模及智能优化研究——基于有限理性及中国情景的视觉”(项目编号:71271138) 上海理工大学国家级项目与文科基地培育计划项目“云制造模式下供应链协同生产调度研究”(项目编号:5812114243)资助
【分类号】：F274;TP3

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