[1]张玉州,叶 亮,郑军帅.基于滚动时域控制的动态外卖配送问题优化[J].计算机技术与发展,2019,29(10):83-88.[doi:10. 3969 / j. issn. 1673-629X. 2019. 10. 018]
　ZHANG Yu-zhou,YE Liang,ZHENG Jun-shuai.Optimization of Dynamic Takeaway Distribution Problem Based on Receding Horizon Control[J].,2019,29(10):83-88.[doi:10. 3969 / j. issn. 1673-629X. 2019. 10. 018]
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基于滚动时域控制的动态外卖配送问题优化()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年10期
页码:
83-88
栏目:
应用开发研究
出版日期:
2019-10-10

文章信息/Info

Title:
Optimization of Dynamic Takeaway Distribution Problem Based on Receding Horizon Control
文章编号:
1673-629X(2019)10-0083-06
作者:
张玉州; 叶 亮; 郑军帅
安庆师范大学 计算机与信息学院,安徽 安庆 246133
Author(s):
ZHANG Yu-zhou; YE Liang; ZHENG Jun-shuai
School of Computer and Information,Anqing Normal University,Anqing 246133,China
关键词:
外卖配送; 滚动时域控制; 最近邻域算法; 车辆路径规划问题
Keywords:
delivery distribution; receding horizon control; nearest neighbor algorithm; vehicle routing problem
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 10. 018
摘要:
为降低外卖配送过程中的运输费用和提高客户的满意度,现以外卖配送服务总延误时间最短为研究目标,设计了一种基于滚动时域控制的外卖配送问题模型。 该模型将一段时间内的外卖生成订单,按多个时间窗口进行划分,并采用最近邻域算法对订单的位置进行路径搜索,在配送服务中,结合多种状态下利用滚动时域控制策略最大程度地筛选出存在动态干扰的订单,优化配送服务路径。 最后,以某餐饮商户的外卖服务自负配送模型作为算例,对比了两种经典算法FCFS 和 NN。 仿真实验结果表明,该模型在拥挤、正常、非拥挤、高频率扰动、低频率扰动等五种状态下均能够显著降低配送的总延误时间,缩短外卖配送距离,可为外卖平台商户改善配送服务质量和提升客户满意度提供决策支持。
Abstract:
In order to reduce the transportation cost and improve customer satisfaction in the delivery process,a delivery problem model based on receding horizon control is designed to minimize the total delivery delay. The model will be a period of time of delivery to generate orders and divide them into several time windows. The nearest neighbor algorithm is used to search the location of the order. In distribution services,receding horizon control strategy is used to select the order with dynamic disturbance to the greatest extent and optimize the distribution service path. Finally,a catering businesses delivery service self-conceited distribution model is taken as an example to compare two classical algorithms,FCFS and NN. The simulation shows that the model can significantly reduce the total delay time of delivery and shorten the delivery distance under five conditions:congestion,normal,non-congestion,high-frequency disturbance and low-frequency disturbance,which can provide decision-making support for take-out platform merchants to improve service quality and customer satisfaction.
更新日期/Last Update: 2019-10-10