| 云制造平台下基于蝙蝠算法的供需调度时间优化 |
| |
| 引用本文： | 武超然,李芳,江海涛.云制造平台下基于蝙蝠算法的供需调度时间优化[J].现代情报,2014,34(10):35-40. |
| |
| 作者姓名： | 武超然 李芳 江海涛 |
| |
| 作者单位： | 上海理工大学管理学院, 上海200093 |
| |
| 基金项目： | 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”，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” |
| |
| 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.
|
| 关 键 词： | 云制造 供应链 蝙蝠算法 任务调度 最优时间 |
Time Optimization of Supply and Demand Scheduling Based on Bat Algorithm Under the Cloud Manufacturing Platform |
| |
| Authors: | Wu Chaoran Li Fang Jiang Haitao |
| |
| Institution: | Business School, University of Shanghai for Science and Technology, Shanghai 200093, China |
| |
| Abstract: | Cloud manufacturing platform offers a variety of choices for building supply chain.There are lots of data about the supply chain scheduling and the data frequently update.To solve this problem, the bat algorithm(BA)was coded and decoded newly.The improved bat algorithm(IBA)limited the generation of initial population and solved the problem about batch scheduling.As a result, it reduced the invalid search and shortened the time of finding the right tasks strategy.By experimental comparison, the effectiveness of the IBA was proved.IBA avoided the phenomenon of resource overload and idle resources, which promotes the application of cloud manufacturing in the supply chain. |
| |
| Keywords: | |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《现代情报》浏览原始摘要信息 |
| 点击此处可从《现代情报》下载免费的PDF全文 |
|
