多目标卫星数传调度蚁群优化算法

Ant Colony Optimization algorithm for multi-objective satellite data transmission scheduling

卫星数传调度问题具有任务多、资源少、调度约束复杂等特点,为满足多目标优化调度的理论和现实需要,提出了多目标卫星数传调度蚁群优化算法。算法建立了基于任务调度关系的解构造图,提出了用于可行解构造的自适应伪随机概率决策模型,以及基于Pareto解偏离度的全局信息素更新策略。仿真结果表明,算法具有较好的Pareto前沿收敛性,各优化目标都能得到较好的指标评价值,所获得的Pareto解集规模适度,Pareto解的多样性、分布均匀性和散布范围都较好。

Satellite data transmission scheduling problem with more tasks,less resources,complex scheduling constraint and other characteristics,to satisfy the demand of theory and practical multi-objective optimization scheduling,the ant colony optimization algorithm for satellite data transmission scheduling is proposed.The algorithm builds up solution construction graph based on the scheduling relations between tasks,and puts forward a self-adaptive pseudo random proportional probability decision-making model for constructing feasible solutions,as well as the global pheromone updating strategy based on deviation degree of Pareto solutions.Simulation results show that,the proposed algorithm has better Pareto frontier convergence.The optimized objectives can get a better index evaluation value.The scale of Pareto solutions obtained is appropriate.Pareto solutions of diversity,distribution uniformity and spreading scope are better.