【摘要】 应用于航空航天的重载AGV对调度系统的稳定性和工作效率提出了更高的要求，运用基于理想解法的模拟退火遗传算法对某航空公司的重载钻铆AGV的调度系统进行设计和实验。首先将AGV当前状态转化为综合评价指数，建立综合评价函数，以此得到遗传算法的适应度函数。然后将模拟退火算法融入遗传算法中，降低了遗传算法容易陷入局部最优解的概率，使得算法具有更高的求解效率。最后经过仿真与试验，提出的算法实际调度时间比基于理想解法的遗传算法调度时间减少11.2%,比模拟退火遗传算法所需时间减少18.6%。有效证明提出的算法具有更强的鲁棒性，减少了算法计算时间和调度时间，提高了调度系统效率。更多还原

【Abstract】 The heavy-duty AGV used in aerospace puts forward higher requirements for the stability and efficiency of the scheduling system. In the paper, the simulated annealing genetic algorithm based on ideal solution was used to design and experiment the scheduling system of heavy-duty drilling and riveting AGV of an airline. First, the current state of the AGV was transformed into a comprehensive evaluation index, and a comprehensive evaluation function was established to obtain the fitness function of the genetic algorithm. Then the simulated annealing algorithm was integrated into the genetic algorithm, which reduces the probability that the genetic algorithm is easy to fall into the local optimal solution, and makes the algorithm more efficient. Finally, simulations and experiments prove that the algorithm proposed in this paper is more robust, reduces the calculation time and scheduling time of the algorithm, and improves the efficiency of the scheduling system.更多还原