CAJ | 학술논문

提出了一种求解多星成像调度问题的基于分解的优化算法，将问题分解为任务分配主问题与单星成像调度子问题．任务分配主问题生成不同卫星的任务分配方案，单星成像调度子问题则根据分配的任务进行优化，生成每颗卫星的成像调度方案．采用自适应的蚁群算法求解任务分配主问题，通过自适应参数调整策略及信息素平滑策略，实现全局搜索和快速收敛间的平衡．采用启发式算法及快速模拟退火算法求解单星成像调度子问题，通过综合多颗卫星的调度结果，可以对任务分配方案进行评价，引导蚁群算法搜索优化的任务分配方案，最终得到多颗卫星的成像调度方案．大规模测试算例验证了算法的效率．
제출료일충구해다성성상조도문제적기우분해적우화산법，장문제분해위임무분배주문제여단성성상조도자문제．임무분배주문제생성불동위성적임무분배방안，단성성상조도자문제칙근거분배적임무진행우화，생성매과위성적성상조도방안．채용자괄응적의군산법구해임무분배주문제，통과자괄응삼수조정책략급신식소평활책략，실현전국수색화쾌속수렴간적평형．채용계발식산법급쾌속모의퇴화산법구해단성성상조도자문제，통과종합다과위성적조도결과，가이대임무분배방안진행평개，인도의군산법수색우화적임무분배방안，최종득도다과위성적성상조도방안．대규모측시산례험증료산법적효솔．
An optimization algorithm based on decomposition is proposed for solving satellites observation scheduling problem. The problem is decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellites scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy are introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony algorithm, which can guide the search process of ant colony. Computation results show that the approach is effective to the satellites observation scheduling problem.