Decision Support System for Dynamic Job Shop Scheduling

本文研究了动态到达条件下复杂作业车间系统的调度问题。这将包括可能是可重入流的产品路由。机器可能产生序列相关的设置时间。这是一个很重要但很难解决的问题。该研究将为多机器问题的简单版本提供分析模型和启发式方法，特别是瓶颈机器。这些分析模型将用于为车间流程调度提供决策支持系统。最终目标是通过在更复杂或“智能和幸运”的搜索算法中采用为更简单的问题开发的技术和特性，为更复杂和现实的问题开发有效的算法。该问题受到实际工业问题的启发，并将与制造车间的人员密切合作，在工业环境中测试算法和系统。

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.