摘要
分析了滚动调度研究的核心问题,即滚动调度窗口工件的选入规则的研究所存在的问题,提出粗神经网络滚动调度窗口工件选入算法。以粗集的方法对实际调度方案中滚动调度窗口工件的实际选入方案进行数据挖掘从而发现滚动调度窗口的选入规则,并以此规则构造神经网络进行计算以判断工件选入与否。并采用粗集的方法对提取的规则中所存在的相互冲突的规则进行了适当的处理。
The essential question of job rolling scheduling is how to select the job into Rolling Scheduling Window（RSW）.Generally,research work always use sample heuristic method as selection rule for RSW,and most research work only consider time factor.However,multi-factors are always considered in the actual scheduling,especially priority and time.This study,therefore,propose to use rough-set to mine the selection rules for RSW from actual scheduling when the priority and time are considered synchronously, and use the rule to construct neural network to calculate which job will be selected into RSW. A rough-set method is proposed to deal with some rules conflicted to each other.
出处
《组合机床与自动化加工技术》
北大核心
2010年第1期104-107,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
863重点项目(2007AA040604)
山东省自然科学基金(Y2006F23)
关键词
滚动调度
滚动调度窗口
选入规则
粗集
神经网络
规则冲突
rolling scheduling
window of rolling scheduling
selection rule
rough sets
neural network
conflict resolution
