A co-evolutionary algorithm with elite archive strategy for generating diverse high-quality satellite range schedules

Abstract

AbstractSatellite range scheduling, a multi-constrained combinatorial optimization problem, is crucial to guaranteeing the normal operation and application of onboard satellites. Traditional methods are dedicated to finding one optimal schedule, having ignored the problem may process multiple high-quality schedules. To provide a set of alternative schedules while maintaining the solution quality, we propose a co-evolutionary algorithm with elite archive strategy (COEAS) in this article. In COEAS, two populations are evolved to solve the original and relaxed problem in terms of schedule quality and diversity, respectively. During the evolution, the populations maintain a weak cooperation and only share the information in offspring combination phase. Further, an elite archive strategy is derived to identify and preserve potential stagnated and optimal individuals. In this strategy, the promising individuals would further participate in parent mating and offspring replacement for the dual purpose of maintaining potential optima recovery and fine-tuning the population. The experimental results show that the proposed algorithm is better than comparison algorithms in terms of efficacy (obtaining higher quality schedule), diversity (locating more optimal schedules) and flexibility (providing better alternatives).