Resource Scheduling for Space-based Early Warning System Based on Improved Particle Swarm Optimization

Resource Scheduling for Space-Based Early Warning System is an important but intractable problem.Traits of Early Warning tasks are analyzed first,and then a task decomposition method is presented to convert the tasks to a solvable combination optimization problem,which is formulated by a Constraint Satisfaction Problem(CSP)model.Since the CSP model contains many variables and has a large scale,an improved Particle Swarm Optimization(PSO)algorithm was designed.The algorithm has a high capability in solution space searching,and can avoid being premature through a convergent preventing mechanism.Experimental results show that the algorithm can obtain the desired scheduling schemes in a given short period.