| Peer-Reviewed

Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application

Received: 28 October 2021    Accepted: 24 November 2021    Published: 2 December 2021
Views:       Downloads:
Abstract

In the modern society with highly developed logistics, while paying attention to structural and functional strategic layout and global scale services, it is also our ultimate goal to pursue efficient transportation / high-quality logistics services, reduce logistics transportation costs and reduce CO2 emissions. This paper proposes a new concept of multi warehouse collaborative distribution Vehicle Dispatching Problem (VDP/MD) and its customization, and provides a solver for complex scenarios in real new transportation problems. Aiming at the VDP/MD problem, an enhanced computing model with hierarchical and multiple structure is introduced, which is calledHIMS++computing model. It consists of three layers: the atomic layer is the fluctuation area of system regulation cost, the molecular layer is the formation area of system stable state, and the individual layer is the optimization decision area of scheduling plan. TheHIMS++model is constructed by using object-oriented programming software components; The optimization algorithm is realized by heuristic probability exploration and fuzzy decision-making method. The experiment was carried out using the 3-day order data obtained from the actual dispatching center in Tokyo Metropolitan Area, which has 27 oil tank vehicles (including 2 types). It is proved that theHIMS++model is more accurate (10% improvement) and faster (12 times) than the results given by experts.HIMS++model is also a convenient tool to solve the actual transportation combination optimization problem (multi parameter, multi constraint and multi-objective optimization problem), This study introduces a novel solution for digital logistics support and accurate Vehicle distribution scheduling.

Published in Science Discovery (Volume 9, Issue 6)
DOI 10.11648/j.sd.20210906.31
Page(s) 401-409
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Vehicle Dispatching, HIMS Calculation Model, Tabu Search, Fuzzy Inference, Object-oriented Paradigm

References
[1] Xinguo Shuia, Xingquan Zuoa, Cheng Chena and Alice E. Smithb, A clonal selection algorithm for urban bus vehicle scheduling, Applied Soft Computing, vol. 36 pp 36-44, (2015).
[2] Wu, Z, Optimization of distribution route selection based on particle swarm algorithm, International Journal of Simulation Modelling, pp 230-242, (2014).
[3] Ehsan M, Azizolah J, Homa A and Rashed S, A novel transportation location routing network for the sustainable closed-loop supply chain considering the quality of returns, vol. 10, Journal of Remanufacturing, Amsterdam, pp 79-106, (2020).
[4] Maaike H, Yossiri A, Wout D and Patrick J, The Robust Vehicle Routing Problem with Time Window, vol. 55, Transportation Science, (2021).
[5] Afifi S, Dang D and Moukrim A, A Simulated Annealing Algorithm for the Vehicle Routing Problem with Time Windows and Synchronization Constraints 7th International Conference, Learning and Intelligent Optimization (LION7) (Catania, Italy). Pp 259-65, (2013).
[6] Gallo C and Capozzi V July A Simulated Annealing Algorithm for Scheduling Problems, Journal of Applied Mathematics and Physics pp 2579-94, (2019).
[7] Cheeneebash J and Nadal C, Using Tabu Search Heuristics in Solving the Vehicle Routing Problem with Time Windows: Application to a Mauritian Firm. (2010).
[8] Dorner K and Schilde M February, The Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows (Johannes Kepler Universitat Linz), (2017).
[9] Jordan M, Yi M, Juergen B, Mengjie Z, Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems, vol. 28, Evolutionary Computation, pp 563-593, (2020).
[10] Lee LH, Chew EP, Tan KC and Wang YA, Vehicle dispatching algorithms for container transshipment hubs, vol. 32, OR SPECTRUM, pp 663-685, (2010).
[11] Fang Huang, Dingsheng Liu, Xiaowen Li, Lizhe Wang and Wenbo Xu, Preliminary study of a cluster-based open-source parallel GIS based on the GRASS GIS, International Journal of Digital Earth, vol. 4 pp 402-420, (2011).
[12] Shulin Lan, Hao Zhang, Ray. Y Zhong and G. Q. Huang, A customer satisfaction evaluation model for logistics services using fuzzy analytic hierarchy process, Industrial Management & Data Systems, vol. 116 pp 1024-1042, (2016).
[13] Chen K, Dong F and Hirota K, A Calculation Model of Hierarchical Multiplex Structure with Fuzzy Inference for VRSD Problem, Recent Development in Fuzzy logic and fuzzy sets, Studies in Fuzziness and Soft Computing (Springer Science and Business Media), Vol 391 pp 175-99, (2020).
[14] Guo Jinjin, Zhang Huiying, Sun Guie and Mu Zhendong, Transportation Path Optimization of Modern Logistics Distribution considering Hybrid Tabu Search Algorithm, vol. 2021, Advances in Multimedia, (2021).
[15] Julian Lee and David Perkins, A simulated annealing algorithm with a dual perturbation method for clustering, Pattern Recognition, vol. 112, (2020).
Cite This Article
  • APA Style

    Kewei Chen, Fangyan Dong, Xusheng Wang, Yuecong Zhu, Xiaomin Chu, et al. (2021). Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application. Science Discovery, 9(6), 401-409. https://doi.org/10.11648/j.sd.20210906.31

    Copy | Download

    ACS Style

    Kewei Chen; Fangyan Dong; Xusheng Wang; Yuecong Zhu; Xiaomin Chu, et al. Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application. Sci. Discov. 2021, 9(6), 401-409. doi: 10.11648/j.sd.20210906.31

    Copy | Download

    AMA Style

    Kewei Chen, Fangyan Dong, Xusheng Wang, Yuecong Zhu, Xiaomin Chu, et al. Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application. Sci Discov. 2021;9(6):401-409. doi: 10.11648/j.sd.20210906.31

    Copy | Download

  • @article{10.11648/j.sd.20210906.31,
      author = {Kewei Chen and Fangyan Dong and Xusheng Wang and Yuecong Zhu and Xiaomin Chu and Kaoru Hirota},
      title = {Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application},
      journal = {Science Discovery},
      volume = {9},
      number = {6},
      pages = {401-409},
      doi = {10.11648/j.sd.20210906.31},
      url = {https://doi.org/10.11648/j.sd.20210906.31},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20210906.31},
      abstract = {In the modern society with highly developed logistics, while paying attention to structural and functional strategic layout and global scale services, it is also our ultimate goal to pursue efficient transportation / high-quality logistics services, reduce logistics transportation costs and reduce CO2 emissions. This paper proposes a new concept of multi warehouse collaborative distribution Vehicle Dispatching Problem (VDP/MD) and its customization, and provides a solver for complex scenarios in real new transportation problems. Aiming at the VDP/MD problem, an enhanced computing model with hierarchical and multiple structure is introduced, which is calledHIMS++computing model. It consists of three layers: the atomic layer is the fluctuation area of system regulation cost, the molecular layer is the formation area of system stable state, and the individual layer is the optimization decision area of scheduling plan. TheHIMS++model is constructed by using object-oriented programming software components; The optimization algorithm is realized by heuristic probability exploration and fuzzy decision-making method. The experiment was carried out using the 3-day order data obtained from the actual dispatching center in Tokyo Metropolitan Area, which has 27 oil tank vehicles (including 2 types). It is proved that theHIMS++model is more accurate (10% improvement) and faster (12 times) than the results given by experts.HIMS++model is also a convenient tool to solve the actual transportation combination optimization problem (multi parameter, multi constraint and multi-objective optimization problem), This study introduces a novel solution for digital logistics support and accurate Vehicle distribution scheduling.},
     year = {2021}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Research on Vehicle Scheduling Problem of Multi Warehouse Collaborative Distribution and Its Application
    AU  - Kewei Chen
    AU  - Fangyan Dong
    AU  - Xusheng Wang
    AU  - Yuecong Zhu
    AU  - Xiaomin Chu
    AU  - Kaoru Hirota
    Y1  - 2021/12/02
    PY  - 2021
    N1  - https://doi.org/10.11648/j.sd.20210906.31
    DO  - 10.11648/j.sd.20210906.31
    T2  - Science Discovery
    JF  - Science Discovery
    JO  - Science Discovery
    SP  - 401
    EP  - 409
    PB  - Science Publishing Group
    SN  - 2331-0650
    UR  - https://doi.org/10.11648/j.sd.20210906.31
    AB  - In the modern society with highly developed logistics, while paying attention to structural and functional strategic layout and global scale services, it is also our ultimate goal to pursue efficient transportation / high-quality logistics services, reduce logistics transportation costs and reduce CO2 emissions. This paper proposes a new concept of multi warehouse collaborative distribution Vehicle Dispatching Problem (VDP/MD) and its customization, and provides a solver for complex scenarios in real new transportation problems. Aiming at the VDP/MD problem, an enhanced computing model with hierarchical and multiple structure is introduced, which is calledHIMS++computing model. It consists of three layers: the atomic layer is the fluctuation area of system regulation cost, the molecular layer is the formation area of system stable state, and the individual layer is the optimization decision area of scheduling plan. TheHIMS++model is constructed by using object-oriented programming software components; The optimization algorithm is realized by heuristic probability exploration and fuzzy decision-making method. The experiment was carried out using the 3-day order data obtained from the actual dispatching center in Tokyo Metropolitan Area, which has 27 oil tank vehicles (including 2 types). It is proved that theHIMS++model is more accurate (10% improvement) and faster (12 times) than the results given by experts.HIMS++model is also a convenient tool to solve the actual transportation combination optimization problem (multi parameter, multi constraint and multi-objective optimization problem), This study introduces a novel solution for digital logistics support and accurate Vehicle distribution scheduling.
    VL  - 9
    IS  - 6
    ER  - 

    Copy | Download

Author Information
  • College of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, China

  • College of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, China

  • Graduate College of Engineering and Technology, Fudan University, Shanghai, China

  • Graduate College of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, China

  • Graduate College of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, China

  • Automation College, Beijing Institute of Technology, Beijing, China

  • Sections