Title :
Space Surveillance Resource Scheduling based on GA
Author :
Qing-qing Yan ; Huai-rong Shen ; Qiong-ling Shao
Author_Institution :
Equip. Acad., Beijing, China
Abstract :
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.
Keywords :
aerospace instrumentation; genetic algorithms; scheduling; space research; surveillance; GA; chromosome; forcing mutation; genetic algorithm; integral serial number; observation resources; reduced window; space object; space surveillance resource scheduling; visible window; Aerospace electronics; Automation; Genetic algorithms; Intelligent control; Prototypes; Space vehicles; Surveillance; genetic algorithm; resource scheduling; space surveillance;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053536