Optimization Scheduling Design of Monitoring Resources using a Process-improved Adaptive Genetic Algorithm
Man Zhao, Dongcheng Li, Lei Zhang, Liu Hu, Shou-Yu Lee · 2021
The rising quantity of space debris in outer space has endangered the operation of satellites and occupied many available orbital resources. In this context, the most pressing task is to clarify the way of effectively monitoring space debris through reasonably scheduling and allocating monitoring equipment. In this paper, optimization scheduling problems of monitoring equipment are first solved using the process-improved adaptive genetic algorithm. Then, the elitism strategy is added to the basic process of the algorithm for improving the selection operator. The improved algorithm is superior to the traditional one because it provides a better solution to the local convergence problem and significantly accelerates the convergence speed. In addition, the effectiveness of the improved algorithm is thoroughly verified through various experiments and comparative analysis.