考虑客户满意度的物流末端节点选址模型及算法

doi:10.3969/j.issn.1007-7375.2019.03.016

工业工程 ›› 2019, Vol. 22 ›› Issue (3): 126-131.doi: 10.3969/j.issn.1007-7375.2019.03.016

• 实践与应用 • 上一篇

考虑客户满意度的物流末端节点选址模型及算法

肖玉徽¹, 楼振凯²

1. 海口经济学院工商管理学院, 海南海口 571127;
2. 北京理工大学管理与经济学院, 北京 100081

收稿日期:2018-11-21 出版日期:2019-06-30 发布日期:2019-06-27
作者简介:肖玉徽(1984-),女,四川省人,讲师,主要研究方向为区域物流、快递物流
基金资助:
海南省哲学社会科学规划资助项目（HNSK（YB）16-57）；海口经济学院校级重点科研资助项目（hjkz18-04）

A Model and an Algorithm of Logistics Terminal Node Location Problem Considering Customer Satisfaction

XIAO Yuhui¹, LOU Zhenkai²

1. College of Business Administration, Haikou University of Economics, Haikou 571127, China;
2. School of Management & Economics, Beijing Institute of Technology, Beijing 100081, China

Received:2018-11-21 Online:2019-06-30 Published:2019-06-27

摘要/Abstract

摘要： 为了解决自取货的物流末端单一节点选址问题，在服务顾客数量和地理位置已知的前提下，考虑最远取货距离的约束，建立以客户满意度模糊隶属度为目标函数的数学模型。为了求解该模型，运用均值聚类给出初始可行节点，以满意度较小的客户为顶点，在分析其合理性的基础上，设计基于三角形外心和等分点的启发式算法优化初始解，算法允许接受一次次优解以避免陷入局部最优，并通过记忆数组来跟踪搜索过程，最终输出过程最优解。最后给出算例分析，证明了所提出的图上寻优算法优于均值聚类和点密度聚类算法。

关键词: 最远取货距离, 客户满意度, 均值聚类, 三角形外心

Abstract: In order to solve the location problem of single logistics terminal node of picking up goods by self-help pattern, the constraint of farthest distance is considered under the premise that customers' number and geographical location are given, and a mathematical model is established with the objective function of the fuzzy membership degree of customer satisfaction. For the purpose of solving the model, the means clustering is applied to obtain an initial feasible node, and then a heuristic algorithm is proposed to optimize the initial solution based on excentre of triangle and equal diversion point by taking customers of less satisfaction as vertexes, which allows to accept one-time suboptimum solution in order to avoid falling into local optimum. In addition, a memory array is set to ensure that final output is optimal solution throughout the process. Finally, a numerical example is given, which demonstrates that the heuristic algorithm is better than both the means clustering and the point density clustering.

Key words: farthest distance of pick up goods, customer satisfaction, means clustering, excentre of triangle

中图分类号:

F252

肖玉徽, 楼振凯. 考虑客户满意度的物流末端节点选址模型及算法[J]. 工业工程, 2019, 22(3): 126-131.

XIAO Yuhui, LOU Zhenkai. A Model and an Algorithm of Logistics Terminal Node Location Problem Considering Customer Satisfaction[J]. Industrial Engineering Journal , 2019, 22(3): 126-131.

参考文献

[1] 陈义友, 韩珣, 曾倩. 考虑送货上门影响的自提点多目标选址问题[J]. 计算机集成制造系统, 2016, 22(8):1-18 CHEN Yiyou, HAN Xun, ZENG Qian. Multi-objective pickup point location problem considering impact of home delivery[J]. Computer Integrated Manufacturing Systems, 2016, 22(8):1-18
[2] 倪冠群, 徐寅峰, 徐玖平. 考虑道路通行能力的应急避难点选址模型及算法[J]. 中国管理科学, 2015, 23(1):82-88 NI Guanqun, XU Yinfeng, XU Jiuping. The location models and algorithms for emergency shelter with traffic capacity constraint[J]. Chinese Journal of Management Science, 2015, 23(1):82-88
[3] 代文锋, 仲秋雁, 贺冬冬. 基于灰理想关联熵的应急物资配送中心选址[J]. 系统工程, 2016, 34(4):101-108 DAI Wenfeng, ZHONG Qiuyan, HE Dongdong. Locating the distribution center of the emergency materials based on grey ideal correlation entropy[J]. Systems Engineering, 2016, 34(4):101-108
[4] 韦忆立, 高咏玲. 含时间约束的配送中心选址和能力规划的鲁棒优化[J]. 统计与决策, 2015(1):49-53 WEI Yili, GAO Yongling. Robust optimization of distribution center location and capacity planning with time constraints[J]. Statistics and Decision, 2015(1):49-53
[5] 唐东明, 朱清新, 杨凡. 基于仿射传播聚类的大规模选址布局问题求解[J]. 计算机应用研究, 2010, 27(3):841-844 TANG Dongming, ZHU Qingxin, YANG Fan. Solving large scale location problem using affinity propagation clustering[J]. Application Research of Computers, 2010, 27(3):841-844
[6] BOUJELBEN M K, GICQUEL C, MINOUX M. A MILP model and heuristic approach for facility location under multiple operational constraints[J]. Computers & Industrial Engineering, 2016, 98(8):446-461
[7] 周翔, 许茂增, 吕奇光. B2C模式下配送中心与末端节点的两阶段布局优化模型[J]. 计算机集成制造系统, 2014, 20(12):3140-3149 ZHOU Xiang, XU Maozeng, LYU Qiguang. Two-stage layout optimization model for distribution center and terminal node under B2C mode[J]. Computer Integrated Manufacturing Systems, 2014, 20(12):3140-3149
[8] 刘颖莹, 刘培玉, 王智昊. 一种基于密度峰值发现的文本聚类算法[J]. 山东大学学报(理学版), 2016, 51(1):65-71 LIU Yingying, LIU Peiyu, WANG Zhihao. A text clustering algorithm based on find of density peaks[J]. Journal of Shandong University (Natural Science), 2016, 51(1):65-71
[9] LYIGUN C. The planar hub location problem:a probabilistic clustering approach[J]. Annals of Operations Research, 2013, 211(1):193-207
[10] 戴阳阳, 李朝锋, 徐华. 初始点优化与参数自适应的密度聚类算法[J]. 计算机工程, 2016, 42(1):203-209 DAI Yangyang, LI Chaofeng, XU Hua. Density clustering algorithm with initial point optimization and parameter self-adaption[J]. Computer Engineering, 2016, 42(1):203-209
[11] 岳志新, 陈晓楠, 索继东. 基于FCM聚类的雷达中频信号的运动目标检测[J]. 大连海事大学学报, 2015, 41(3):124-127 YUE Zhixin, CHEN Xiaonan, SUO Jidong. Target detection of radar IF signal based on FCM clustering[J]. Journal of Dalian Maritime University, 2015, 41(3):124-127
[12] 宫尚宝, 郭玉翠. 基于遗传算法的模糊聚类分析[J]. 模糊系统与数学, 2010, 24(6):123-128 GONG Shangbao, GUO Yucui. Genetic algorithm based on fuzzy cluster analysis[J]. Fuzzy Systems and Mathematics, 2010, 24(6):123-128
[13] WANG Huaixiao, ZHU Wanhong, LIU Jianyong, et al. Multi-distribution center location based on real-parameter quantum evolutionary clustering algorithm[J]. Mathematical Problems in Engineering, 2014, 2014:1-7
[14] 肖建华, 王飞, 白焕新. 基于非等覆盖半径的生鲜农产品配送中心选址[J]. 系统工程学报, 2015, 30(3):406-416 XIAO Jianhua, WANG Fei, BAI Huanxin. Location of distribution centers for fresh agricultural products based on non-equal coverage radius[J]. Journal of Systems Engineering, 2015, 30(3):406-416
[15] 曾山. 模糊聚类算法研究[D]. 武汉:华中科技大学, 2012. ZENG Shan. Research on fuzzy clustering algorithm[D]. Wuhan:Huazhong University of Science and Technology, 2012.

考虑客户满意度的物流末端节点选址模型及算法

A Model and an Algorithm of Logistics Terminal Node Location Problem Considering Customer Satisfaction

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

本文评价

[1]	张和平, 李俊武. 基于模糊c均值聚类算法的控制图模式识别[J]. 工业工程, 2021, 24(5): 108-116.
[2]	李玉民, 邱梦, 黑柏林, 方曾利. 考虑高铁时间窗和客户满意度的生鲜品公铁联运路径选择[J]. 工业工程, 2021, 24(2): 49-56.
[3]	户佐安, 贾叶子, 李博威, 刘陆. 考虑客户满意度的车辆路径优化研究[J]. 工业工程, 2019, 22(1): 100-107.
[4]	罗建强, 吴启飞, 李昊, 冯庆华. 交互视角下产品服务系统方案优选模型[J]. 工业工程, 2017, 20(3): 15-22.
[5]	张炎亮1，胡琳琳1，李亚东2. 基于神经网络集成的第三方物流客户满意度测评[J]. 工业工程, 2013, 16(3): 84-88.