Modeling Local Search: A First Step Toward Understanding Hill-climbing Search in Oversubscribed Scheduling

Previous results for a real-world domain, scheduling communications requests for the Air Force Satellite Control Network (AFSCN), suggested that the best search methods perform a greedy random walk. We examine the degree to which this observation is accurate for AFSCN by modeling a next-descent hill-climbing search as a Markov process. We find that the model is somewhat accurate for AFSCN. To generalize, we apply this model to another oversubscribed scheduling problem: scheduling image requests for a set of Earth Observing Satellites (EOS). We find that the hill-climber follows a trajectory that can be modeled as a Markov