Efficient satellite scheduling based on improved vector evaluated genetic algorithm

被引：17

作者：

Mao, Tengyue ^{[1
,2
]}

Xu, Zhengquan ^{[1
]}

Hou, Rui ^{[2
]}

Peng, Min ^{[1
]}

机构：

[1] State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan

[2] College of Computer Science, South-Central University for Nationalities, Wuhan

来源：

Journal of Networks | 2012年 / 7卷 / 03期

关键词：

Dividing Pareto front; Multi-objective optimization; Satellite scheduling; VEGA;

D O I：

10.4304/jnw.7.3.517-523

中图分类号：

学科分类号：

摘要：

Satellite scheduling is a typical multi-peak, manyvalley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm) based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research, multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling. © 2012 ACADEMY PUBLISHER.

引用

页码：517 / 523

页数：6

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