The past decade has seen an increase in the number of satellites in orbit and in highly dynamic satellite requests, making the control by ground stations inefficient. The traditional management composed of ground planning with separate onboard execution is seriously lagging in response to dynamically incoming tasks. To meet the demand for the real-time response to emergent events, a multi-autonomous-satellite system with a central-distributed collaborative architecture was formulated by an integer programming model. Based on the structure, evolutionary rules were proposed to solve this problem by the use of sequence solution construction and a constructed heuristic method based on gene expression programming evolution. First, the features of the problem are extracted based on domain knowledge, then, the problem-solving rules are evolved by gene expression programming. The simulation results reflect that the evolutionary rule completely surpasses the three types of heuristic rules with adaptive mechanisms and achieves a solution effect close to meta-heuristic algorithms with a reasonably fast solving speed.

Multi-objective energy management for PHEV using Pontryagin's minimum principle and particle swarm optimization online SCIENCE CHINA Information Sciences 64, 119204 (2021); Multi-objective optimization of shock control bump on a supercritical wing SCIENCE CHINA Technological Sciences 57, 192 (2014); Intersection signal control multi-objective optimization based on genetic algorithm

No abstract

No abstract