基于O2O的大型零售企业城市配送网络优化研究

doi:10.16381/j.cnki.issn1003-207x.2017.09.018

中国管理科学 ›› 2017, Vol. 25 ›› Issue (9): 159-167.doi: 10.16381/j.cnki.issn1003-207x.2017.09.018

基于O2O的大型零售企业城市配送网络优化研究

赵泉午^1,2, 赵军平^1,2, 林娅²

1. 重庆大学经济与工商管理学院, 重庆 400030;
2. 重庆大学现代物流重庆市重点实验室, 重庆 400030

收稿日期:2016-01-29 修回日期:2016-10-14 出版日期:2017-09-20 发布日期:2017-11-24
作者简介:赵泉午(1976-),男(汉族),河南方城人,重庆大学经济与工商管理学院教授,博士,研究方向:现代物流与供应链管理、营销渠道及零售管理,E-mail:zhaoquanwu@126.com.
基金资助:
重庆市社会科学规划一般项目（2015YBGL109）；国家自然科学基金资助项目（71002070）；国家社会科学基金重点项目（14AGL023）；国家科技支撑计划资助项目（2015BAH46F01）

A City Logistics Network Optimization Model for Large Chain Retailers under Online-Offline Channel Integration

ZHAO Quan-wu^1,2, ZHAO Jun-ping^1,2, LIN Ya²

1. School of Economics and Business Administration, Chongqing University, Chongqing 400030, China;
2. Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing 400030, China

Received:2016-01-29 Revised:2016-10-14 Online:2017-09-20 Published:2017-11-24

摘要/Abstract

摘要： 本文研究了O2O转型背景下大型零售企业城市配送网络优化面临的中转中心选址及末端需求点分配问题，构建了考虑配送中心到末端需求点近似配送距离的中转中心选址及末端需求点分配联合优化模型，设计了集成遗传算法和禁忌搜索算法的混合算法求解模型，通过混合算法与CPLEX的对比证明了本文算法的有效性。以苏宁重庆主城核心区域的城市配送网络优化为实例进行测算，给出了苏宁重庆主城核心区域中转中心的选址及需求点分配的联合优化方案。联合优化方案表明城市物流"最后一公里"末端配送成本占城市物流总成本的比例超过60%；车型是影响城市物流总成本的关键因素，选择与中转中心容量接近的车型能够显著降低城市物流总成本，减少运输距离；合理的中转中心选择能提高短距离配送比例和减少配送总距离。

关键词: O2O转型, 选址-分配, &ldquo, 最后一公里&rdquo, 遗传算法, 禁忌搜索算法

Abstract: In this article, joint location-assignment problem is studied for designing an Urban Logistics Network (ULN) with multiple intermediate depots (IDs) and terminals of ULN. The key decisions are where to locate the intermediate depots (IDs) and how to assign terminals to IDs such that the total network cost is minimized. A large-scale static and deterministic integer programming model is presented solving a joint location-assignment problem of large chain retailers. To solve this model, a more efficient hybrid algorithm integrated with Genetic algorithm and Tabu search algorithm is put forward based on heuristic searching criteria. Our methodology is illustrated with the Urban Logistics Network from a leading Chinese retailer (Suning) in Chongqing. Numerical analysis suggests that optimal solutions can reduce the total network cost between 2.92%~14.36% by comparison with the current ULN.Delivery costs of "Last Mile" account for total urban logistics network costs more than 60%. Vehicle type is a deterministic factor to total urban logistics network costs. The effects of changing parameter values on the optimal solutions are also studied and some management implications are pointed out.

Key words: online-offline channel integration, iocation-assignment problem, “last mile”, Genetic algorithm, tabu search algorithm

中图分类号:

U121
O221

赵泉午, 赵军平, 林娅. 基于O2O的大型零售企业城市配送网络优化研究[J]. 中国管理科学, 2017, 25(9): 159-167.

ZHAO Quan-wu, ZHAO Jun-ping, LIN Ya. A City Logistics Network Optimization Model for Large Chain Retailers under Online-Offline Channel Integration[J]. Chinese Journal of Management Science, 2017, 25(9): 159-167.

参考文献

[1] Aikens C H. Facility location models for distribution Planning[J]. European Journal of Operational Research, 1985, 22(3):263-279.

[2] Shen Z J M, Coullard C, Daskin M S. A joint location-Inventory model[J]. Transportation Science, 2003, 37(1):40-55.

[3] Tsao Y C, Mangotra D, Lu J C, et al. A continuous approximation approach for the integrated facility-inventory allocation problem[J]. European Journal of Operational Research, 2012, 22(2):216-228.

[4] Taniguchi E, Noritake M, Yamada T, et al. Optimal size and location planning of public logistics terminals[J]. Transportation Research, 1999, 35(3):207-222.

[5] Wang Yong, Ma Xiaolei, Xu Maozeng,et al.Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization-genetic algorithm[J]. Expert Systems with Applications, 2015,42(12):5019-5031.

[6] Diabat A, Battaïa O, Nazzal D. An improved Lagrangian relaxation-based heuristic for a joint location-inventory problem[J]. Computers & Operations Research, 2015, 61:170-178.

[7] Ahmadi-Javid A, Hoseinpour P. A Location-inventory-pricing model in a supply chain distribution network with price-sensitive demands and inventory-capacity constraints[J]. Transportation Research Part E:Logistics and Transportation Review, 2015, 82:238-255.

[8] Jouzdani J, Sadjadi S J, Fathian M. Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty:A case of Tehran[J].Applied Mathematical Modeling, 2013, 37(18-19):8467-8483.

[9] 唐金环, 戢守峰, 朱宝琳. 考虑碳配额差值的选址-路径-库存集成问题优化模型与算法[J]. 中国管理科学, 2014, 22(9):114-122.

[10] 杨珺, 卢巍. 低碳政策下多容量等级选址与配送问题研究[J]. 中国管理科学, 2014, 22(5):51-60.

[11] 赵泉午, 杨茜. 考虑CO₂排放量的城市专业物流中心选址研究[J]. 中国管理科学, 2014, 22(7):124-130.

[12] Diabat A, Al-Salem M. An integrated supply chain problem with environmental considerations[J]. International Journal of Production Economics, 2015, 164:330-338.

[13] 刘必争, 毛超. 电子商务下的配送中心选址问题及其优化[J]. 系统工程, 2008, 26(10):17-20.

[14] 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.

[15] 蒋忠中, 汪定伟. B2C电子商务中配送中心选址问题及其优化[J]. 控制与决策, 2005, 20(10):1125-1128.

[16] Xu Bin, Wei Chunli, Shi Zhanjiang, et al. Study on location-selection of B2C e-commerce logistics distribution center[C]//Proceedings of 2009 International Forum on Computer Science-Technology and Applications,Chongqing,China,December 25-27,2009.

[17] Torabi S A, Hassini E, Jeihoonian M. Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing[J]. Transportation Research Part E:Logistics and Transportation Review,2015,79:128-144.

[18] Yu V F, Lin S Y. A simulated annealing heuristic for the open location-routing problem[J]. Computers & Industrial Engineering, 2015, 62:184-196.

[19] 关菲, 张强. 模糊多目标物流配送中心选址模型及其求解算法[J]. 中国管理科学, 2013,21(S1):57-62.

[20] Lau H C W, Jiang Zhongzhong, Ip W H, et al. A credibility-based fuzzy location model with Huriwicz criteria for the desingn of distribution systems in B2C e-commerce[J]. Computers & Industrial Engineering, 2010, 59:873-886.

[21] 张晓楠, 范厚明, 李剑锋. B2C物流配送网络双目标模糊选址模型与算法[J]. 系统工程理论与实践, 2015, 35(5):1202-1213.

[22] Nadizadeh A, Nasab HH. Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm[J]. European Journal of Operational Research, 2014, 238(2):458-470.

[23] Eilon S, Waston-Gandy C D T, Christofides N. Distribution management:Mathematical modelling and practical analysis[M]. New York:Hafner, 1971.

[24] Daganzo C F. The distance traveled to visit N points with a maximum of C stops per vehicle:An Analytic Model and an Application[J]. Transportation Science, 1984, 18(4):331-350.

[25] Figliozzi M A. Planning approximations to the average length of vehicles routing problems with varying customer demands and routing constraints[J]. Transportation Research Record:Journal of the Transportation Research Board, 2008, 2089:1-8.

[26] Davis B A, Figliozzi M A. A methodology to evaluate the competitiveness of electric delivery trucks[J]. Transportation Research Part E:Logistics and Transportation Review, 201349:8-23.

[27] 周愉峰, 马祖军, 王恪铭. 应急物资储备库的可靠性P-中位选址模型[J]. 管理评论, 2015, 27(5):198-208.

基于O2O的大型零售企业城市配送网络优化研究

A City Logistics Network Optimization Model for Large Chain Retailers under Online-Offline Channel Integration

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