RANDOM WALKS AND NEIGHBORHOOD BIAS IN OVERSUBSCRIBED SCHEDULING

This paper presents new results showing that a very simple stochastic hill climbing algorithm is as good or better than more complex metaheuristic methods for solving an oversubscribed scheduling problem: scheduling communication contacts on the Air Force Satellite Control Network (AFSCN). The empirical results also suggest that the best neighborhood construction choices produce a search that is largely a greedy random walk of the graph induced by the complete neighborhood.