Auction mechanism-based order allocation for third-party vehicle logistics platforms

被引:2
作者
Chen, Zhiyang [1 ]
You, Jiapeng [1 ]
Jiang, Hongwei [1 ]
Ming, Xinguo [1 ]
Sun, Poly Z. H. [1 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Ind Engn, Shanghai 200240, Peoples R China
关键词
Vehicle logistics platform; Auction mechanism; Order allocation; RESOURCE-ALLOCATION; PROCUREMENT; OPTIMIZATION; FRAMEWORK; INTERNET;
D O I
10.1016/j.aei.2023.102116
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
By integrating social transportation capacity and matching transportation needs, third-party vehicle logistics platforms could efficiently make full use of logistics resources and reduce logistics costs. For a vehicle logistics platform in the future, the adopted strategy for order allocation determines whether the platform could win the competition in a complex business environment to a large extent. After investigating the order allocation ideas proposed by designers of third-party vehicle logistics platforms, we find these ideas typically lead to low efficiency of transportation and cannot solve the problem that is difficult for platforms to obtain accurate information. Besides, it also can be seen that the current order allocation idea rarely considers the impact of goodwill on the platform. To conduct a more efficient order allocation for third-party vehicle logistics platforms, this paper proposes a new allocation method based on the auction mechanism. The proposed auction method could achieve the long-term operation of platforms by weighing and adjusting the revenue of platforms and fleets with second price. According to experiments and analysis, the allocation method proposed in this paper can be more effectively applied to solve the order allocation problem of vehicle logistics platforms than other compared methods, which helps platforms to achieve better economic benefits and goodwill in long-term operations.
引用
收藏
页数:16
相关论文
共 53 条
  • [1] BAUMOL WJ, 1983, AM ECON REV, V73, P491
  • [2] A holistic relook at engineering design methodologies for smart product-service systems development
    Cong, Jing-chen
    Chen, Chun-Hsien
    Zheng, Pai
    Li, Xinyu
    Wang, Zuoxu
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 272
  • [3] Operations management of smart logistics: A literature review and future research
    Feng, Bo
    Ye, Qiwen
    [J]. FRONTIERS OF ENGINEERING MANAGEMENT, 2021, 8 (03) : 344 - 355
  • [4] Pushing frontiers in auction-based transport collaborations
    Gansterer, Margaretha
    Hartl, Richard F.
    Sorensen, Kenneth
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2020, 94 (94):
  • [5] Multi-modal transportation planning for multi-commodity rebalancing under uncertainty in humanitarian logistics
    Gao, Xuehong
    Jin, Xuefeng
    Zheng, Pai
    Cui, Can
    [J]. ADVANCED ENGINEERING INFORMATICS, 2021, 47
  • [6] Task Allocation in Spatial Crowdsourcing: Current State and Future Directions
    Guo, Bin
    Liu, Yan
    Wang, Leye
    Li, Victor O. K.
    Lam, Jacqueline C. K.
    Yu, Zhiwen
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (03): : 1749 - 1764
  • [7] An auction-enabled collaborative routing mechanism for omnichannel on-demand logistics through transshipment
    Guo, Chaojie
    Thompson, Russell G.
    Foliente, Greg
    Kong, Xiang T. R.
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2021, 146
  • [8] Mathematical Modeling and Optimization of Platform Service Supply Chains: A Literature Review
    Guo, Xiaotong
    He, Yong
    [J]. MATHEMATICS, 2022, 10 (22)
  • [9] A dynamic newsvendor problem with goodwill-dependent demands and minimum commitment
    Han, Xiaoya
    Yu, Yugang
    Hu, Guiping
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2019, 89 : 242 - 256
  • [10] A bi-objective supplier location, supplier selection and order allocation problem with green constraints: scenario-based approach
    Hemmati, Maryam
    Pasandideh, Seyed Hamid Reza
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 12 (08) : 8205 - 8228