Q-learning was applied to resolution of the adaptive dispatching rule selection problem under dynamic single-machine scheduling environment.
提出了一种利用Q-学习解决动态单机调度环境下的自适应调度规则选择的方法。
Through the analysis of the problem, it is proved that the problem is equivalent to a single-machine scheduling for minimizing an analogous function of delay.
基于对问题的分析，证明了这一问题等价于单机调度中极小化类似的延迟量函数。
We consider a single machine scheduling problem involving both the processing and scheduling of job delivery.
本文考虑了一个包含工件生产和工件送货的单机调度问题。
The improved tabu algorithm of single machine scheduling with job class setups is proposed.
基于改进禁忌搜索算法，建立了此类单机成组作业调度模型，可搜索到该问题的最优解。
Minimize the total weighted completion time single machine scheduling problems.
最小化加权总完工时间的单机排序问题。
The single machine scheduling problem with continuous resources is discussed.
讨论具有连续资源的单机排序问题。
A single machine-scheduling problem with fuzzy delays and mixed precedence relations is discussed.
分析了一类带有模糊时间延迟和混合优先关系的单机调度问题。
A single machine-scheduling problem with fuzzy delays and mixed precedence relations is discussed.
分析了一类带有模糊时间延迟和混合优先关系的单机调度问题。
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