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首页 > 过刊浏览>2023年第39卷第6期 >111-122. DOI:10.16544/j.cnki.cn43-1494/u.2022100223121966
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冷链物流多式联运路径选择优化研究
CSTR:
[cstr]
作者:
作者单位:

(1.河海大学 土木与交通学院，江苏 南京 210098;2.苏交科集团股份有限公司，江苏 南京 210019)

作者简介:

郑长江（1966—），男，河海大学教授，博士生导师。Email:zheng@hhu.edu.cn

中图分类号:

U15

基金项目:

国家自然科学基金项目（71801080）


Research on the routing optimization for cold chain logistics multimodal transportation
Author:
Affiliation:

(1.College of Civil Engineering and Transportation Engineering, HoHai University, Nanjing 210098, China;2. JSTI Group, Nanjing 210019, China)

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    摘要:

    为降低冷链食品（CCF）在运输过程中的总成本，提高客户满意度，采用多式联运对冷链食品进行物流配送。先基于多式联运网络、总成本最小化和客户满意度最大化，构建路径选择模型；再采用改进粒子群优化算法(IPSO)对模型进行求解；最后，利用实际案例进行模型验证和敏感性分析。研究结果表明：与公路单式联运相比，多式联运的运输成本降低了13.4%，总成本降低了2.4%，时间满意度提高了3.3%，总满意度提高了0.6%。通过提升铁路运输速度，可有效地降低运输总成本,提高客户满意度。

    Abstract:

    In order to reduce the total cost of cold chain food (CCF) multimodal transportation process and improve customer satisfaction, this paper proposes the study of Cold Chain Food logistics routing optimization by multi-modal transportation. Based on the multimodal transportation network, the path selection model is constructed considering the minimization of total cost and the maximization of customer satisfaction. The improved particle swarm optimization algorithm (IPSO) was used to solve the model. Finally, the model verification and sensitivity analysis are carried out using real cases. The analysis results show that the transportation cost of multimodal transportation is reduced by 13.4%, the total cost is reduced by 7.2%, the time satisfaction is increased by 3.3%, and the total satisfaction is increased by 0.6%. By improving the speed of railway transportation, the total transportation cost can be effectively reduced and customer satisfaction can be improved.

    参考文献
    [1] 胡元, 帅宇红. 整车物流运输多式联运与路径优化研究[J]. 交通运输工程与信息学报, 2019, 17(1): 13-18. DOI: 10.3969/j.issn.1672-4747.2019.01.003.HU Yuan, SHUAI Yuhong. Multimodal transportation and route optimization of vehicle logistics[J]. Journal of Transportation Engineering and Information, 2019, 17(1): 13-18. DOI: 10.3969/j.issn.1672-4747.2019.01.003.
    [2] HEI X L, MENG Q A, WANG S A, et al. Optimal automobile distribution model in multimodal freight transportation networks[J]. Transportation Research Record: Journal of the Transportation Research Board, 2014, 2410(1): 50-57. DOI: 10.3141/2410-06.
    [3] MOCCIA L, CORDEAU J F, LAPORTE G, et al. Modeling and solving a multimodal transportation problem with flexible-time and scheduled services[J]. Networks, 2011, 57(1): 53-68. DOI: 10.1002/net.20383.
    [4] 李玉民, 邱梦, 闫凯丽, 等. 高铁参与下考虑时间窗的生鲜品多式联运路径选择[J]. 重庆交通大学学报(自然科学版), 2021, 40(4): 54-61.LI Yumin, QIU Meng, YAN Kaili, et al. Multimodal transportation route selection of fresh products considering time window with the participation of high-speed rail[J]. Journal of Chongqing Jiaotong University (Natural Science), 2021, 40(4): 54-61.
    [5] 刘松, 邵毅明, 彭勇. 转运限制下的冷藏集装箱多式联运路径优化[J]. 计算机应用与软件, 2020, 37(7): 37-42. DOI: 10.3969/j.issn.1000-386x.2020.07.006.LIU Song, SHAO Yiming, PENG Yong. Multimodal transport path optimization for refrigerated containers under transshipment limit[J]. Computer Applications and Software, 2020, 37(7): 37-42. DOI: 10.3969/j.issn.1000-386x.2020.07.006.
    [6] YU Y L, XIAO T J. Analysis of cold-chain service outsourcing modes in a fresh agri-product supply chain[J]. Transportation Research Part E: Logistics and Transportation Review, 2021, 148: 102264. DOI: 10.1016/j.tre.2021.102264.
    [7] ZHANG S Y, CHEN N, SONG X M, et al. Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy[J]. Transportation Research Part A: Policy and Practice, 2019, 130: 844-857. DOI: 10.1016/j.tra.2019.10.004.
    [8] 崔亚琼. 以铁路物流中心为节点的多式联运探究[J]. 新西部, 2020(14): 17-18.CUI Yaqiong. Research on multimodal transport with railway logistics center as the node[J]. New West, 2020(14): 17-18.
    [9] 侯海录. 铁路集装箱多式联运发展策略研究[J]. 交通运输工程与信息学报, 2018, 16(1): 56-60.HOU Hailu. Research on the development strategy of multimodal transport by railway container[J]. Journal of Transportation Engineering and Information, 2018, 16(1): 56-60.
    [10] 朱欣媛, 赵建有, 张璐璐, 等. 碳排放约束下考虑模糊时间窗的多式联运路径选择[J]. 物流科技, 2020, 43(11): 77-82. DOI: 10.13714/j.cnki.1002-3100.2020.11.019.ZHU Xinyuan, ZHAO Jianyou, ZHANG Lulu, et al. Path selection of multimodal transportation considering fuzzy time window under carbon emission constraint[J]. Logistics Sci-Tech, 2020, 43(11): 77-82. DOI: 10.13714/j.cnki.1002-3100.2020.11.019.
    [11] 李畅, 陈淮莉. 基于新鲜度和配送成本的易腐食品配送路径[J]. 上海海事大学学报, 2019, 40(1): 14-20, 36. DOI: 10.13340/j.jsmu.2019.01.003.LI Chang, CHEN Huaili. Distribution route of perishable food based on freshness and distribution cost[J]. Journal of Shanghai Maritime University, 2019, 40(1): 14-20, 36. DOI: 10.13340/j.jsmu.2019.01.003.
    [12] 欧阳瑞祥, 周和平, 刘静波, 等. 时变路网下机场接驳车辆-用户共享路径优化[J]. 交通科学与工程, 2020, 36(3): 88-93. DOI: 10.16544/j.cnki.cn43-1494/u.2020.03.014.OUYANG Ruixiang, ZHOU Heping, LIU Jingbo, et al. Airport feeder vehicle-user shared path optimization under time-varying network[J]. Journal of Transport Science and Engineering, 2020, 36(3): 88-93. DOI: 10.16544/j.cnki.cn43-1494/u.2020.03.014.
    [13] 郭权, 周和平, 欧阳瑞祥, 等. 动态信息下的机场定制巴士路径优化[J]. 交通科学与工程, 2021, 37(2): 85-90. DOI: 10.16544/j.cnki.cn43-1494/u.2021.02.013.GUO Quan, ZHOU Heping, OUYANG Ruixiang, et al. Route optimization of customized airport bus base on dynamic information[J]. Journal of Transport Science and Engineering, 2021, 37(2): 85-90. DOI: 10.16544/j.cnki.cn43-1494/u.2021.02.013.
    [14] 杨艳, 黄晴, 龙思, 等. 基于ARIMA-LSTM的货运量组合预测方法研究[J]. 交通科学与工程, 2022, 38(2): 102-108. DOI: 10.16544/j.cnki.cn43-1494/u.2022.02.011.YANG Yan, HUANG Qing, LONG Si, et al. Research on combined forecasting method of freight volume based on ARIMA-LSTM[J]. Journal of Transport Science and Engineering, 2022, 38(2): 102-108. DOI: 10.16544/j.cnki.cn43-1494/u.2022.02.011.
    [15] 王清洲, 张玉宁, 陈佳梦, 等. 基于Witness仿真的绿色多式联运路径优化[J]. 大连海事大学学报, 2020, 46(3): 22-30. DOI: 10.16411/j.cnki.issn1006-7736.2020.03.003.WANG Qingzhou, ZHANG Yuning, CHEN Jiameng, et al. Path optimization of green multimodal transport based on Witness simulation[J]. Journal of Dalian Maritime University, 2020, 46(3): 22-30. DOI: 10.16411/j.cnki.issn1006-7736.2020.03.003.
    [16] 陈钉均, 李尧, 倪少权, 等. 收货时间窗软约束下绿色多式联运路径优化[J]. 计算机仿真, 2020, 37(4): 209-214.CHEN Dingjun, LI Yao, NI Shaoquan, et al. Optimal path of green multimodal transport under soft constraint of receipt time window[J]. Computer Simulation, 2020, 37(4): 209-214.
    [17] 辜勇, 李雨, 陈句, 等. 多式联运碳减排研究综述[J]. 物流技术, 2021, 40(9): 1-5. DOI: 10.3969/j.issn.1005-152X.2021.09.001.GU Yong, LI Yu, CHEN Ju, et al. Summary of researches on carbon emissions reduction in multimodal transport[J]. Logistics Technology, 2021, 40(9): 1-5. DOI: 10.3969/j.issn.1005-152X.2021.09.001.
    [18] 孙家庆, 王胜男, 闫淑贤. 考虑碳排放的冷藏集装箱多式联运路径选择[J]. 大连海事大学学报, 2022, 48(2): 57-65. DOI: 10.16411/j.cnki.issn1006-7736.2022.02.007.SUN Jiaqing, WANG Shengnan, YAN Shuxian. Path selection of multimodal transport for refrigerated containers considering carbon emission[J]. Journal of Dalian Maritime University, 2022, 48(2): 57-65. DOI: 10.16411/j.cnki.issn1006-7736.2022.02.007.
    [19] LIU S C, ZHANG C. Optimization of urban cold chain transport routes under time-varying network conditions[J]. Journal of Advanced Transportation, 2021, 2021: 1-16. DOI: 10.1155/2021/8817991.
    [20] BABAGOLZADEH M, SHRESTHA A, ABBASI B, et al. Sustainable cold supply chain management under demand uncertainty and carbon tax regulation[J]. Transportation Research Part D: Transport and Environment, 2020, 80: 102245. DOI: 10.1016/j.trd.2020.102245.
    [21] BORTOLINI M, FACCIO M, FERRARI E, et al. Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization[J]. Journal of Food Engineering, 2016, 174: 56-67. DOI: 10.1016/j.jfoodeng.2015.11.014.
    [22] RADHIKA K, ARUN PRAKASH K. Multi-objective optimization for multi-type transportation problem in intuitionistic fuzzy environment[J]. Journal of Intelligent & Fuzzy Systems, 2022, 43(1): 1439-1452. DOI: 10.3233/jifs-213517.
    [23] 晏远春, 刘浩学, 张永, 等. 基于模糊TOPSIS的道路危险货物运输企业安全评价方法[J]. 中国安全科学学报, 2010, 20(9): 32-37. DOI: 10.16265/j.cnki.issn1003-3033.2010.09.004.YAN Yuanchun, LIU Haoxue, ZHANG Yong, et al. A methodology for safety assessment of hazardous material road transport enterprises based on fuzzy TOPSIS[J]. China Safety Science Journal (CSSJ), 2010, 20(9): 32-37. DOI: 10.16265/j.cnki.issn1003-3033.2010.09.004.
    [24] MENG L Y, ZHOU X S. An integrated train service plan optimization model with variable demand: a team-based scheduling approach with dual cost information in a layered network[J]. Transportation Research Part B: Methodological, 2019, 125: 1-28. DOI: 10.1016/j.trb.2019.02.017.
    [25] 蒲松, 王文宪, 陈钉均, 等. 高速旅客列车开行方案的鲁棒优化模型[J]. 交通运输系统工程与信息, 2015, 15(6):101-106. DOI: 10.16097/j.cnki.1009-6744.2015.06.016.PU Song, WANG Wenxian, CHEN Dingjun, et al. The robust model for line planning problems of high speed passenger train[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(6): 101-106. DOI: 10.16097/j.cnki.1009-6744.2015.06.016.
    [26] 樊昊煜, 黄志鹏. 考虑旅客出行满意度的高铁列车开行方案优化[J]. 铁道科学与工程学报, 2021, 18(8): 2006-2012. DOI: 10.19713/j.cnki.43-1423/u.T20200939.FAN Haoyu, HUANG Zhipeng. Optimization of the train operation scheme on high-speed railways considering the satisfaction of passenger travel[J]. Journal of Railway Science and Engineering, 2021, 18(8): 2006-2012. DOI: 10.19713/j.cnki.43-1423/u.T20200939.
    [27] 张春田, 戚建国, 杨立兴, 等. 基于不确定旅客需求的高速铁路鲁棒列车开行方案研究[J]. 交通运输系统工程与信息, 2022, 22(1): 115-123. DOI: 10.16097/j.cnki.1009-6744.2022.01.013.ZHANG Chuntian, QI Jianguo, YANG Lixing, et al. Robust train operation plan based on uncertain passenger demands for high-speed railway corridors[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 115-123. DOI: 10.16097/j.cnki.1009-6744.2022.01.013.
    [28] 薛锋, 范千里, 罗建. 基于多层复杂网络的轨道交通产业链优化[J]. 交通运输工程与信息学报, 2021, 19(2): 65-73, 83. DOI: 10.3969/j.issn.1672-4747.2021.02.007.XUE Feng, FAN Qianli, LUO Jian. Optimization of rail transit industry chain based on multi-layer complex networks[J]. Journal of Transportation Engineering and Information, 2021, 19(2): 65-73, 83. DOI: 10.3969/j.issn.1672-4747.2021.02.007.
    [29] FATHI A, KARIMI B, SAEN R F. Sustainability assessment of supply chains by a novel robust two-stage network DEA model: a case study in the transport industry[J]. Soft Computing, 2022, 26(13): 6101-6118. DOI: 10.1007/ s00500-022-07013-y.
    [30] BRUNS F, GOERIGK M, KNUST S, et al. Robust load planning of trains in intermodal transportation[J]. OR Spectrum, 2014, 36(3): 631-668. DOI: 10.1007/ s00291-013-0341-8.
    [31] VANKERSCHAVER K, WILLOCX F, SMOUT C, et al. Mathematical modeling of temperature and gas composition effects on visual quality changes of cut endive[J]. Journal of Food Science, 1996, 61(3): 613-620. DOI: 10.1111/j.1365-2621.1996.tb13170.x.
    [32] MA Q L, WANG W Y, PENG Y, et al. An optimization approach to the intermodal transportation network in fruit cold chain, considering cost, quality degradation and carbon dioxide footprint[J]. Polish Maritime Research, 2018, 25(1): 61-69. DOI: 10.2478/pomr-2018-0007.
    [33] LELE? P, WASIAK M. The model of selecting multimodal technologies for the transport of perishable products[J]. Archives of Transport, 2019, 50(2): 17-33. DOI: 10.5604/01.3001.0013.5573.
    [34] KENNEDY J, EBERHART R. Particle swarm optimization[C]//Proceedings of ICNN'95 - International Conference on Neural Networks. November 27 - December 1, 1995, Perth, WA, Australia. IEEE, 1995（4）: 1942-1948. DOI: 10.1109/ICNN.1995.488968.
    [35] SHI Y, EBERHART R C. Empirical study of particle swarm optimization[C]//Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406). July 6-9, 1999, Washington, DC, USA. IEEE, 1999（3）: 1945-1950. DOI: 10.1109/CEC.1999.785511.
    [36] SHI Y, EBERHART R. A modified particle swarm optimizer[C]//1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360). May 4-9, 1998, Anchorage, AK, USA. IEEE, 1998: 69-73. DOI: 10.1109/ICEC.1998.699146.
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郑长江,张晨,陶童统,等.冷链物流多式联运路径选择优化研究[J].交通科学与工程,2023,39(6):111-122.
ZHANG Changjiang, ZHANG Chen, TAO Tongtong, et al. Research on the routing optimization for cold chain logistics multimodal transportation[J]. Journal of Transport Science and Engineering,2023,39(6):111-122.

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  • 收稿日期:2022-10-02
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