Improved Genetic Algorithm with Local Search for Satellite Range Scheduling System and its Application in Environmental monitoring

Abstract

Satellites play an important role in such areas as environmental monitoring and disaster prediction that are related to human survival and development. Satellite monitoring and control is the key to the satellite's management and control of the ground to ensure its smooth implementation. Because of the imbalance of demand and available resources, satellite range scheduling has become particularly important. This paper analyzes the satellite range scheduling problem and sets up mathematical models and constraints. Afterwards, this paper proposes an efficient algorithm that combines improved genetic algorithm and local search method. The improved genetic algorithm is used to rapidly improve the quality of the planning scheme, and the neighborhood search is used for the subsequent small-scale optimization. In order to improve the speed of search, our algorithm uses a reorganization operation and a mutation operation adjusted with the number of iterations. In order to test the effectiveness of the algorithm, we conducted experimental verifications of the calculations of various types of satellites at different mission scales and compared them with other algorithms.