基于改进鱼群算法的双向式立体库货位优化研究

Research on Cargo Optimization of Two-Way Stereoscopic Warehouse Based on Improved Fish Swarm Algorithm

针对现代数字化大型工业立体仓库单一仓位货物数量不定、出入库次数频繁等特点,且多条较长巷道导致的存储效率较低等问题,提出了基于多巷道双向式货物出入库策略,开展货位优化工作。以提高出入库效率、平衡各巷道工作量为目标建立系统货位优化模型,提出了基于平均距离视野的自适应改进人工鱼群算法对该系统进行优化,通过引入视步系数,减少传统鱼群算法对初始参数值的依赖,提高了收敛速度以及收敛值精度。实验结果表明优化效果显著,为现代企业打造基于数字化平台的大型立体库提供了思路,具有重大的研究和实践意义。

Aiming at the characteristics of modern digital large-scale industrial three-dimensional warehouses,such as variable quantity of goods in a single warehouse,frequent inbound and outbound times,and low storage effi-ciency caused by multiple long lanes,a multi lane bidirectional cargo inbound and outbound strategy is proposed to carry out cargo location optimization work.To improve the efficiency of warehouse entry and exit,and balance the workload of each lane,a system cargo location optimization model was established,and an adaptive and improved ar-tificial fish swarm algorithm based on the average distance field of vision was proposed to optimize the system,the de-pendence of the traditional artificial fish algorithm on the initial parameter value was reduced by introducing the step coefficient,and the convergence speed and convergence accuracy were improved.The experimental results show that the optimization effect is remarkable,which provides an idea for modern enterprises to build a large three-dimension-al warehouse based on digital platform,and has great research and practical significance.