Abstract:

We present an interactive jobshop scheduling application developed with the Human-Guided Search (HuGS) framework and toolkit. Our system leverages people's abilities in areas in which they currently outperform computers, and allows people to steer a computer towards effective jobshop schedules based on their knowledge of real-world constraints. Furthermore, users can better understand, justify, and modify schedules if they participate in their construction. Our prototype allows users to manually modify the current schedule, backtrack to previous schedules, and invoke, monitor, and halt a variety of search algorithms to find better schedules. These search algorithms include a variant of tabu search that users can focus and constrain by visually annotating elements of the schedule.