Yan-Jie Song

TL;DR: An improved multi-objective evolutionary algorithm (MOEA) is proposed, called learning-guided nondominated sorting genetic algorithm II (LGNSGAII) that contains a learning mechanism that can speed up optimization process.

TL;DR: This paper first simplified the problem and established a corresponding mathematical model with the hybrid objective of maximizing the profit and task completion rate, and proposed a population perturbation and elimination strategy based genetic algorithm (GA-PE) which focused on the Multi-Satellite TT&C Scheduling problem.

TL;DR: A mix-integer mathematical model based on graph structure of relay satellite system scheduling problem was proposed and knowledge about satellite scheduling was introduced into an evolutionary algorithm, named knowledge-based genetic algorithm (KBGA).

TL;DR: A general data-driven framework-imaging satellite mission planning framework (ISMPF) for solving imaging mission planning problems is proposed and has a strong generality and is suitable for most situations of imaging satellites.

TL;DR: An efficient algorithm is proposed that combines improved genetic algorithm and local search method that is used to rapidly improve the quality of the planning scheme, and the neighborhood search is used for the subsequent small-scale optimization.