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Satellite range scheduling with the priority constraint is one of the most important problems in the field of satellite operation.This paper proposes a station coding based genetic algorithm to solve this problem,which adopts a new chromosome encoding method that arranges tasks according to the ground station ID.The new encoding method contributes to reducing the complexity in conflict checking and resolving,and helps to improve the ability to find optimal resolutions.Three different selection operators are designed to match the new encoding strategy,namely random selection,greedy selection,and roulette selection.To demonstrate the benefits of the improved genetic algorithm,a basic genetic algorithm is designed in which two cross operators are presented,a single-point crossover and a multi-point crossover.For the purpose of algorithm test and analysis,a problem-generating program is designed,which can simulate problems by modeling features encountered in real-world problems.Based on the problem generator,computational results and analysis are made and illustrated for the scheduling of multiple ground stations.
Satellite range scheduling with the priority constraint is one of the most important problems is one of the most important problems in the field of satellite operation. This paper proposes a station coding based genetic algorithm to solve this problem, which adopts a new chromosome encoding method that arranges tasks according to the ground station ID. The new encoding method contributes to reducing the complexity in conflict checking and resolving, and helps to improve the ability to find optimal resolutions.Three different selection operators are designed to match the new encoding strategy, namely random selection, greedy selection, and roulette selection.To demonstrate the benefits of the improved genetic algorithm, a basic genetic algorithm is designed in which two cross operators are presented, a single-point crossover and a multi-point crossover. For the purpose of algorithm test and analysis, a problem- generating program is designed, which can simulate problems by modeling features encountered in real-world problems. Based on th e problem generator, computational results and analysis are made and illustrated for the scheduling of multiple ground stations.