Location method of logistics distribution center based on BP neural network optimized by improved bat algorithm

Dongmei Luo
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Abstract

In order to solve the practical problems of unreasonable results and long time-consuming existing in traditional logistics distribution center location method, this paper introduces improved bat algorithm to optimize BP neural network, and designs a new logistics distribution center location method. This paper analyzes the basic principles of BP neural network and bat algorithm, introduces one-dimensional nonlinear chaotic sequence into bat algorithm, uses the improved algorithm to optimize BP neural network, and uses the optimized network to obtain the location results of logistics distribution center. The experimental results show that the method has good location effect, good convergence performance and low time-consuming.
基于改进bat算法优化的BP神经网络的物流配送中心选址方法
为了解决传统物流配送中心选址方法存在的结果不合理、耗时长等实际问题,本文引入改进的蝙蝠算法对BP神经网络进行优化,设计了一种新的物流配送中心选址方法。分析了BP神经网络和bat算法的基本原理,将一维非线性混沌序列引入到bat算法中,利用改进后的算法对BP神经网络进行优化,并利用优化后的网络得到物流配送中心的选址结果。实验结果表明,该方法定位效果好,收敛性能好,耗时短。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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