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应用微分进化算法(DEA)与字典排序算法(DSA)相结合的智能算法优化管理电子设备动态货位,研究了基于分拣选路径、存取效率、支架稳定性的动态管理多目标优化问题,并与采用遗传算法(GA)的动态管理优化进行了比对,发现字典排序算法能够按照数字顺序大小构建基于分拣选路径、存取效率、支架稳定性等因素重要程度的多目标函数,微分进化算法则能对多目标函数实施有效优化。仿真结果表明,混合智能算法迭代步数少,收敛速度快,具有更好的执行效率。
In this paper, an intelligent algorithm based on differential evolution algorithm (DEA) and dictionary sorting algorithm (DSA) is used to optimize the dynamic position of electronic equipment. The dynamic management multi-objective optimization problem based on sorting routing, access efficiency and stability of scaffold is studied. Compared with the dynamic management optimization using Genetic Algorithm (GA), we find that the dictionary sorting algorithm can construct multi-objective function based on the numerical order size based on the importance of factors such as sorting path, access efficiency and stability of stent. Differential evolution algorithm You can effectively optimize multi-objective functions. Simulation results show that the hybrid intelligent algorithm has fewer iterations, faster convergence speed and better execution efficiency.