Please wait a minute...
浙江大学学报(工学版)
浙江大学学报(工学版)
机械工程     
B2C电商环境下集中式退货中心的车辆调度
张新艳,周健,林婷
同济大学 机械与能源工程学院,上海 201800
Truck scheduling in concentrative reimbursement centre under B2C E-business environment
ZHANG Xin-yan, ZHOU Jian, LIN Ting
School of Mechanical Engineering，Tongji University, Shanghai 201800, China
 全文: PDF(905 KB)   HTML
摘要：

B2C电商环境下集中式退货中心的多出入库车门分配问题增加了车辆调度的复杂度.为解决同时考虑车门分配的集中式退货中心的车辆调度问题,分别给定出入库车门分配策略,提出一种2阶段出入库车门的分配模型.结合此模型以最小化最大完工时间为目标建立数学模型,并结合遗传算法求解最优入库车辆调度序列.设置不同规模的出入库车辆、门以及货物种类进行对比实验,求取随机解和遗传算法得出的最优解,并对2种结果进行对比分析,实验结果表明：在出入库车辆数不超过160的情况下,该模型能够在60 s内给出最优解,且求解时间随着出入库车辆规模和货物种类的增加而增大,遗传算法得出的最优解相对随机解均有一定的改进程度.
Abstract:

In a business to customer (B2C) E-business concentrative reimbursement centre,the multiple inbound and outbound truck-door assignment problem makes its truck scheduling problem much more complicated. A two-stage truck-door assignment model was proposed with given inbound truck-door and outbound truck-door assignment strategies  to solve the truck scheduling problem with considering truck-door assignment simultaneously. And it was applied to establish a mathematical model with the  target function to minimize makespan. Genetic algorithm was integrated to optimize the sequence of inbound trucks. Set experiments under different numbers of inbound and outbound trucks, doors and goods types, computed random solutions and best solutions by Genetic algorithm, then comparatively analyzed these solutions. Experimental results indicated that the optimal solutions could be given in 60s if  numbers of trucks were no more than 160. Computing time increases with the increase of  numbers of trucks and types of goods. Compared with random solutions, genetic algorithm gives solutions that has been improved to a certain degree．
出版日期: 2015-08-28
:  F 224  
作者简介: 张新艳（1974-）,女,讲师,从事生产运作系统规划与仿真研究. E-mail:alicezxy@tongji.edu.cn
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　

引用本文:

张新艳,周健,林婷. B2C电商环境下集中式退货中心的车辆调度[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2015.03.028.

ZHANG Xin-yan, ZHOU Jian, LIN Ting. Truck scheduling in concentrative reimbursement centre under B2C E-business environment. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2015.03.028.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2015.03.028    或    http://www.zjujournals.com/eng/CN/Y2015/V49/I3/598

［1］ WANG Z P, YAO D Q, HUANG P Q. A new location-inventory policy with reverse logistics applied to B2C e-markets of China ［J］.International Journal of Production Economics, 2007, 107(2): 50363．
［2］许婷. 我国B2C电子商务企业的物流配送模式研究及发展策略浅析［J］. 现代商论, 2014, 22(3):58-60．
XU Ting. Analysis and research on distribution strategy and development in B2C enterprises of China ［J］. Modern Business, 2014, 22(3):58-60．
［3］ FLEISCHMANN M, JACQUELINE M, BLOEMHOF R, et al. Quantitative models for reverse logistics: a review ［J］. European Journal of Operational Research, 1997, 103(1): 117．
［4］ 郝建丽. 网络购物中的退货逆向物流研究［J］. 现代营销, 2011, 5:16.
HAO Jian-li. Research on reverse Logistics of online shopping ［J］. Modern Marketing, 2011, 5:16.
［5］ 王妙春, 汪贻生, 姜玉宏. 电子商务环境下逆向物流管理研究［J］. 物流科技, 2013 (1): 115-117．
WANG Miao-chun, WANG Yi-sheng, JIANG Yu-hong. Research on reverse logistics management based on E-business ［J］. Logistics Technology, 2013 (1): 115-117．
［6］ 詹蓉, 陈荣秋. 逆向物流运作管理模型研究［J］. 华中科技大学学报: 自然科学版, 2006,33(10): 115-117．
ZHAN Rong, CHEN Rong-qiu. Model for operations management of reverse logistics ［J］. Journal of Huazhong University of Science and Technology: Natural Science, 2006, 33(10): 115-117．
［7］ BOYSEN N, FLIEDNER M. Cross dock scheduling: classification, literature review and research agenda ［J］. Omega, 2010, 38 (6): 41322．
［8］ VANBELLE J, VALCKENAERS P, CATTRYSSE D. Cross-docking: state of the art ［J］. Omega, 2012, 40(6): 827-846．
［9］ CHEN F, LEE C Y. Minimizing the makespan in a two-machine cross-docking flow shop problem ［J］. European Journal of Operational Research, 2009, 193(1): 59-72.
［10］ WOOYEON Y, EGBELU P J. Scheduling of inbound and outbound trucks in cross docking systems with temporary storage ［J］. European Journal of Operational Research, 2008, 184(1): 377-396．
［11］ BOYSEN N, FLIEDNER M, SCHOLL A. Scheduling inbound and outbound trucks at cross docking terminals ［J］. OR Spectrum, 2010, 32(1): 135-161．
［12］ MIAO Z W, LIM A, MA H. Truck dock assignment problem with operational time constraint within crossdocks ［J］. European Journal of Operational Research, 2009, 192(1): 105-115．
［13］ BERMUDEZ R, COLE M H. A genetic algorithm approach to door assignments in breakbulk terminals ［R］. USA,University of Arkansas∶Mack-Blackwell National Rural Transportation Study Center, 2001．
［14］ KUO Y. Optimizing truck sequencing and truck dock assignment in a cross docking system ［J］. Expert Systems with Applications, 2013, 40(14):5532-5541.
[1] 赵婵媛, 陆志强, 崔维伟. 考虑随机故障的流水线调度问题前摄优化方法[J]. 浙江大学学报(工学版), 2016, 50(4): 641-649.
[2] 寿涌毅, 彭晓峰, 李菲, 赖昌涛. 抢占式资源受限项目调度问题的遗传算法[J]. 浙江大学学报(工学版), 2014, 48(8): 1473-1480.
[3] 庞海云 ,刘南. 基于不完全扑灭的应急物资分配博弈模型[J]. J4, 2012, 46(11): 2068-2072.