Scheduling research has been an active field for the last forty or so years. Over the decades, many techniques have been developed for application to a variety of different problems, and we have learned a lot about how to perform scheduling. There have been some large successes in the application of automated scheduling to real-world problems. However, the reality remains that most scheduling tasks that could potentially benefit from automated scheduling are performed manually, and if not, then by an algorithm that produces highly suboptimal schedules. The question is how to focus future schedulin
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