Solving on agile satellites mission planning based on tabu search-parallel genetic algorithms

Abstract

Agile satellite becomes mainstream development direction in the new generation of earth observation satellite due to its low cost, light weight, a short development cycles and high accuracy of attitude adjustment. Its mission planning problem is NP-hard difficult characteristics because of satellite attitude maneuver ability. A mathematical model of multi-objective for agile satellite mission planning problem is built on the basis of analysis of the agile satellite observations manner and observational characteristics in this paper, and tabu search-parallel genetic algorithm which designed algorithm encoding structure, genetic manipulation and the flow of entire framework and algorithm is proposed. The results that were analyzed by simulation case indicated the effectiveness and speed of the proposed algorithms which are superior to Immune Clonal Selection Algorithm and Adaptive Ant Colony Algorithm.