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Compensation and profit distribution for cooperative green pickup and delivery problem

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  • Wang, Junwei
  • Yu, Yang
  • Tang, Jiafu

Abstract

Cooperation is a powerful strategy to achieve the objective of the green pickup and delivery problem (GPDP) that minimizes carbon emissions of pickup and delivery service. However, the cooperative GPDP may not be accepted by all the partners, as the cost of cooperative GPDP may be higher than that of the non-cooperative minimum cost PDP. Therefore, a reasonable compensation mechanism is desired to form an acceptable cooperative GPDP, and a fair method of profit distribution, based on the mechanism, is needed to stabilize the cooperation. In this paper, we analyze the situations in which a compensation is needed and develop the lower bound of the compensation. Further, we propose an exact method to calculate the actual compensation and the profit distribution based on cooperative game theory. The proposed exact method can efficiently solve the largest scale instance in Li & Lim benchmarks, i.e., pdptw1000-LR1_10_1 with 1,054 customers and 19,306 products. The proposed compensation and profit distribution mechanism based on cooperative game theory is also applied to a real-world GPDP and achieve satisfactory performance. Some interesting and important managerial insights are found and discussed.

Suggested Citation

  • Wang, Junwei & Yu, Yang & Tang, Jiafu, 2018. "Compensation and profit distribution for cooperative green pickup and delivery problem," Transportation Research Part B: Methodological, Elsevier, vol. 113(C), pages 54-69.
    • Handle: RePEc:eee:transb:v:113:y:2018:i:c:p:54-69
    DOI: 10.1016/j.trb.2018.05.003
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    Cited by:

    1. Shaojun Chen & Xiaoqing Wu & Jing Wu & Xueqing Hong, 2023. "Program Arrives Home Smoothly: Uncertainty-Based Routing Scheduling of Home-Based Elderly Care Programs," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    2. Song, Zhuzhu & Tang, Wansheng & Zhao, Ruiqing & Zhang, Guoqing, 2022. "Implications of government subsidies on shipping companies’ shore power usage strategies in port," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    3. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    4. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    5. Öner, Nihat & Kuyzu, Gültekin, 2021. "Core stable coalition selection in collaborative truckload transportation procurement," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    6. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem, 2021. "Green vehicle routing problem: A state-of-the-art review," Post-Print hal-03182944, HAL.
    7. Shejun Deng & Yingying Yuan & Yong Wang & Haizhong Wang & Charles Koll, 2020. "Collaborative multicenter logistics delivery network optimization with resource sharing," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    8. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Yiming Liu & Yang Yu & Yu Zhang & Roberto Baldacci & Jiafu Tang & Xinggang Luo & Wei Sun, 2023. "Branch-Cut-and-Price for the Time-Dependent Green Vehicle Routing Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 14-30, January.
    10. Sun, Wei & Yu, Yang & Wang, Junwei, 2019. "Heterogeneous vehicle pickup and delivery problems: Formulation and exact solution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 181-202.
    11. Yu, Yang & Wang, Sihan & Wang, Junwei & Huang, Min, 2019. "A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 511-527.
    12. Shi, Yong & Boudouh, Toufik & Grunder, Olivier, 2019. "A robust optimization for a home health care routing and scheduling problem with consideration of uncertain travel and service times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 52-95.
    13. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    14. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    15. Liu, Jia-Cai & Sheu, Jiuh-Biing & Li, Deng-Feng & Dai, Yong-Wu, 2021. "Collaborative profit allocation schemes for logistics enterprise coalitions with incomplete information," Omega, Elsevier, vol. 101(C).
    16. Yu, Yang & Wu, Yuting & Wang, Junwei, 2019. "Bi-objective green ride-sharing problem: Model and exact method," International Journal of Production Economics, Elsevier, vol. 208(C), pages 472-482.
    17. Arjun Paul & Ravi Shankar Kumar & Chayanika Rout & Adrijit Goswami, 2021. "A bi-objective two-echelon pollution routing problem with simultaneous pickup and delivery under multiple time windows constraint," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 962-993, December.
    18. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2020. "A green delivery-pickup problem for home hemodialysis machines; sharing economy in distributing scarce resources," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).

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