gtoc9 results from the national university of defense technology team nudt

• DOI: 10.5281/zenodo.1139226
• Publication Date: 2018-01-09
• Authors: Zhang Jin; Yang Zhen; Luo Yazhong; Zhu Hai; Zhu Yue-He; Sun Zhenjiang

The ninth edition of the Global Trajectory Optimization Competition (GTOC) series was successfully organized in April 2017, wherein the competitors were called to design a series of missions able to remove a set of 123 orbiting debris pieces while minimizing the overall cumulative cost. A three-level optimization framework of the NUDT Team is presented and an improved Ant colony Optimization Algorithm, a hybrid encoding Genetic Algorithm and an improved Differential Evolution algorithm are applied to solve the complex problem, which combines the dynamic TSP, mixed-integer sequence optimization and perturbed trajectory rendezvous optimization. The result obtained during the competition ranked second in the eventual leaderboard.