On the basis of genetic algorithm improved with elitism-reserved strategy,an adaptive dual-boundary constraint strategy to improve genetic algorithm is put forward innovatively,which can improve search efficiency,and enhance its conver-gence. Experimental data shows that the adaptive dual-boundary constraint improving genetic algorithm is applied to storage dis-tribution of warehouse management,whose average optimization efficiency is increased by 77.8％,and average optimization speed is increased by 62.5％.%在采用精英保留策略改进遗传算法的基础上,创新性地提出一种自适应双边界约束策略来改进遗传算法,使改进后的算法在提升搜索效率上效果显著,收敛性增强.实验数据表明,自适应双边界约束遗传算法应用于仓储管理的储位分配算法的寻优平均效率提升77.8％,寻优平均速度提升62.5％.
展开▼
