Human-guided simple search: combining information visualization and heuristic search

Scheduling, routing, and layout tasks are examples of hard operations-research problems that have broad application in industry. Typical algorithms for these problems combine some form of gradient descent to find local minima with some strategy for escaping nonoptimal local minima and traversing the search space. Our idea is to divide these two subtasks cleanly between human and computer: in our paradigm of human-guided sample search the computer is responsible only for finding local minima using a simple search method; using information visualization, the human identifies promising regions of the search space for the computer to explore, and also intervenes to help it escape nonoptimal local minima. This is a specific example of a more general strategy, that of combining heuristic-search and information-visualization techniques in an interactive system. We are applying our approach to the problem of capacitated vehicle routing with time windows (CVRTW). We describe the design and implementation of our initial prototype, some preliminary results, and our plans for future work.