基于BP神经网络西北地区冷链物流中心选址模型

重庆交通大学学报（社会科学版） ›› 2016, Vol. 16 ›› Issue (5): 45-50.

基于BP神经网络西北地区冷链物流中心选址模型

夏晶1，黄凯2

1.重庆交通大学经济与管理学院，重庆 400074；2.重庆交通大学土木工程学院，重庆400074

收稿日期:2016-07-12 出版日期:2016-10-01 发布日期:2016-11-04
作者简介:夏晶（1993—），女，甘肃金昌人，重庆交通大学经济与管理学院硕士研究生，研究方向：物流工程。
基金资助:
国家社会科学基金重点项目“中巴伊土国际通道多边战略价值及风险评估研究”（16AGJ007）

Location Model of Cold Chain Logistics Center in Northwest China Based on BP Neural Network

XIA Jing1， HUANG Kai2

(1.School of Economy and Management, Chongqing Jiaotong University, Chongqing 400074, China; 2.School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China)

Received:2016-07-12 Online:2016-10-01 Published:2016-11-04

摘要/Abstract

摘要： 冷链物流中心选址是西北地区发展冷链物流的关键步骤，冷链物流中心选址的研究对物流行业响应国家“新丝绸之路”发展战略有重要意义。结合模糊综合评价法，建立四级综合评估体系，运用BP神经网络训练对西北地区冷链物流中心的备选城市进行科学选址与验证分析，得到西北地区冷链物流中心的最优选址方案，并验证误差在允许范围内，为西北地区发展冷链物流提供科学的选址方案。

关键词: 冷链物流, BP神经网络, 模糊综合评价, 西北地区

Abstract: Cold chain logistics center location is a key step in the development of cold chain logistics in northwest region. The research of cold chain logistics center location is of great significance to the development of logistics industry in response to the national “new silk road” policy. Combined with fuzzy comprehensive evaluation method, the four level comprehensive evaluation system was set up. And the BP neural network training was used to analyze the scientific location and verification of the alternative cities of the cold chain logistics center in northwest China. To obtain the optimal location of the cold chain logistics center in the northwest region, and to verify the error within the allowable range, a scientific site selection is provided for the development of cold chain logistics in the northwest region.

Key words: cold chain logistics, BP neural network, fuzzy comprehensive evaluation, northwest China

夏晶1，黄凯2. 基于BP神经网络西北地区冷链物流中心选址模型[J]. 重庆交通大学学报（社会科学版）, 2016, 16(5): 45-50.

XIA Jing1， HUANG Kai2. Location Model of Cold Chain Logistics Center in Northwest China Based on BP Neural Network[J]. , 2016, 16(5): 45-50.