Decision Support System for Dynamic Job Shop Scheduling

本研究将研究一个复杂的调度问题， 动态到货条件下的Job Shop系统。 这将包括产品 可能是可重入流的路由。 机器可能会引发序列- 相关设置时间。 这是一个重要但又困难的问题 迷要解了. 该研究将提供分析模型，以及 多机问题的简单形式的算法 尤其是瓶颈机器。 这些分析 模型将被用来提供一个决策支持系统， 流程调度 最终的目标是开发有效的算法， 更复杂、更现实的问题， 和属性开发的更简单的问题， 复杂或"聪明和幸运"的搜索算法。 这个问题 受到实际工业问题的启发， 与制造车间的人员合作， 工业环境中的算法和系统。

This research will study the problem of scheduling a complex job shop system under dynamic arrivals. This will include product routings that may be reentrant flows. Machines may incur sequence- dependent setup times. This is an important, but difficult problem to solve. The research will provide analytical models as well as heuristics for the simpler versions of the multi-machine problem and, in particular, the bottleneck machines. These analytical models will be used to provide a decision support system for shop flow scheduling. The ultimate goal is to develop efficient algorithms for the more complicated and realistic problems by adopting the techniques and properties developed for the simpler problem in a more sophisticated or "smart and lucky" search algorithm. This problem is inspired by actual industrial problems and will closely collaborate with the personnel of a manufacturing job shop to test the algorithms and systems in an industrial setting.