Space Surveillance Resource Scheduling based on GA

In the Space Surveillance Resource Scheduling Problem, there are many conflicts among visible windows between observation resources and space objects. By pruning the overlaps between conflicting visible windows, then checking the length of reduced windows and forcing those which are shorter than minimum length to mutate in Genetic Algorithm, a better schedule can be obtained. In this paper the problem of space surveillance resource scheduling is modeled, and the chromosome is encoded using the integral serial number of request windows of each space object. An improved Genetic Algorithm based on pruning overlaps and forcing mutation is proposed to solve the problem. The effectiveness and superiority of the presented algorithm have been demonstrated by the simulation results.