时变交通下生鲜配送电动车辆路径优化方法

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (5): 218-225.

时变交通下生鲜配送电动车辆路径优化方法

赵志学^{1, 2}，李夏苗*1

1. 中南大学交通运输工程学院，长沙 410205；2. 湖南工商大学移动商务智能湖南省重点实验室，长沙 410205

收稿日期:2020-07-19 修回日期:2020-08-20 出版日期:2020-10-25 发布日期:2020-10-26
作者简介:赵志学(1982-)，男，河北唐山人，博士生.
基金资助:
国家自然科学基金/National Natural Science Foundation of China(71071165).

Electric Vehicle Route Optimization for Fresh Logistics Distribution Based on Time-varying Traffic Congestion

ZHAO Zhi-xue^{1, 2}, LI Xia-miao¹

1. School of Traffic & Transportation Engineering, Central South University, Changsha 410205, China; 2. Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Technology and Business, Changsha 410205, China

Received:2020-07-19 Revised:2020-08-20 Online:2020-10-25 Published:2020-10-26

摘要/Abstract

摘要：

依据时变交通路网特点设计基于路段划分策略的行驶时间计算方法，综合考虑客户对生鲜产品最低新鲜度约束，车载限制和电动车电量约束，设计三约束决策因子方法.以配送总成本最小为目标，构建时变交通下电动车城市生鲜配送路径优化模型，根据模型特点设计自适应改进的蚁群算法.实验结果表明，本文方法能够根据客户生鲜新鲜度要求，客户属性和路网特性，合理安排发车时间，科学规划配送路径，有效避免交通拥堵；通过算法对比，本文模型和算法能够明显降低配送成本，提高企业经济效益.

关键词: 城市交通, 电动车路径问题, 蚁群算法, 生鲜配送, 时变交通, 新鲜度

Abstract:

The electric vehicle routing planning for fresh logistics distributions based on time- varying traffic conditions is investigated in this paper. With the time- varying traffic network, the calculation method for travel time is designed based on a route section division strategy. A three-constraint decision factor method is designed to consider the minimum product freshness limit, vehicle load constraints, and electric vehicle power constraints. A distribution route optimization model for electric vehicles is established for the urban logistics distribution of fresh products to minimize the total distribution cost. An improved ant colony algorithm is proposed, in which its parameters are adjusted adaptively. Simulation results show that this method can properly arrange the departure time and plan the distribution route to avoid traffic congestion, according to the requirements of product freshness, customer attributes, and road network characteristics. Compared with other algorithms, the proposed model and algorithm can significantly reduce the distribution cost and improve the economic benefits of enterprises.

Key words: urban traffic, electric vehicle routing problem, ant colony algorithm, fresh distribution, time-varying traffic, freshness

中图分类号:

U116.2

赵志学，李夏苗. 时变交通下生鲜配送电动车辆路径优化方法[J]. 交通运输系统工程与信息, 2020, 20(5): 218-225.

ZHAO Zhi-xue, LI Xia-miao. Electric Vehicle Route Optimization for Fresh Logistics Distribution Based on Time-varying Traffic Congestion[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(5): 218-225.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract20138.shtml

http://www.tseit.org.cn/CN/Y2020/V20/I5/218

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