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Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows

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  • Yong Wang

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
    School of Management and Economics, University of Electronic Science and Technology, Chengdu 610054, China)

  • Yingying Yuan

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Xiangyang Guan

    (Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA)

  • Haizhong Wang

    (School of Civil and Construction Engineering, Oregon State University, Corvallis, OR 97330, USA)

  • Yong Liu

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Maozeng Xu

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract

The sustainability and complexity of logistics networks come from the temporally and spatially uneven distributions of freight demand and supply. Operation strategies without considering the sustainability and complexity could dramatically increase the economic and environmental costs of logistics operations. This paper explores how the unevenly distributed demand and supply can be optimally matched through collaborations, and formulates and solves a Collaborative Pickup and Delivery Problem under Time Windows (CPDPTW) to optimize the structures of logistics networks and improve city sustainability and liverability. The CPDPTW is a three-stage framework. First, a multi-objective linear optimization model that minimizes the number of vehicles and the total cost of logistics operation is developed. Second, a composite algorithm consisting of improved k-means clustering, Demand-and-Time-based Dijkstra Algorithm (DTDA) and Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is devised to solve the optimization model. The clustering algorithm helps to identify the feasible initial solution to INSGA-II. Third, a method based on improved Shapley value model is proposed to obtain the collaborative alliance strategy that achieves the optimal profit allocation strategy. The proposed composite algorithm outperforms existing algorithms in minimizing terms of the total cost and number of electro-tricycles. An empirical case of Chongqing is employed to demonstrate the efficiency of the proposed mechanism for achieving optimality for logistics networks and realizing a win-win situation between suppliers and consumers.

Suggested Citation

  • Yong Wang & Yingying Yuan & Xiangyang Guan & Haizhong Wang & Yong Liu & Maozeng Xu, 2019. "Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows," Sustainability, MDPI, vol. 11(12), pages 1-30, June.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:12:p:3492-:d:242892
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    1. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    2. Li, Hongqi & Liu, Yinying & Jian, Xiaorong & Lu, Yingrong, 2018. "The two-echelon distribution system considering the real-time transshipment capacity varying," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 239-260.
    3. Kumoi, Yuki & Matsubayashi, Nobuo, 2014. "Vertical integration with endogenous contract leadership: Stability and fair profit allocation," European Journal of Operational Research, Elsevier, vol. 238(1), pages 221-232.
    4. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2017. "Benefit allocation for distributed energy network participants applying game theory based solutions," Energy, Elsevier, vol. 119(C), pages 384-391.
    5. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    6. Hafezalkotob, Ashkan & Makui, Ahmad, 2015. "Cooperative maximum-flow problem under uncertainty in logistic networks," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 593-604.
    7. Yong Wang & Shouguo Peng & Kevin Assogba & Yong Liu & Haizhong Wang & Maozeng Xu & Yinhai Wang, 2018. "Implementation of Cooperation for Recycling Vehicle Routing Optimization in Two-Echelon Reverse Logistics Networks," Sustainability, MDPI, vol. 10(5), pages 1-27, April.
    8. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    9. Cruijssen, Frans & Borm, Peter & Fleuren, Hein & Hamers, Herbert, 2010. "Supplier-initiated outsourcing: A methodology to exploit synergy in transportation," European Journal of Operational Research, Elsevier, vol. 207(2), pages 763-774, December.
    10. Jian Li & Yang Li & Panos M. Pardalos, 2016. "Multi-depot vehicle routing problem with time windows under shared depot resources," Journal of Combinatorial Optimization, Springer, vol. 31(2), pages 515-532, February.
    11. Zhang, Yuli & Max Shen, Zuo-Jun & Song, Shiji, 2017. "Lagrangian relaxation for the reliable shortest path problem with correlated link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 501-521.
    12. Wang, Zheng, 2018. "Delivering meals for multiple suppliers: Exclusive or sharing logistics service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 496-512.
    13. Eren Akyol, Derya & De Koster, René B.M., 2018. "Determining time windows in urban freight transport: A city cooperative approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 34-50.
    14. Tu, Wei & Fang, Zhixiang & Li, Qingquan & Shaw, Shih-Lung & Chen, BiYu, 2014. "A bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 84-97.
    15. Liu, Tian & Luo, Zhixing & Qin, Hu & Lim, Andrew, 2018. "A branch-and-cut algorithm for the two-echelon capacitated vehicle routing problem with grouping constraints," European Journal of Operational Research, Elsevier, vol. 266(2), pages 487-497.
    16. Frisk, M. & Göthe-Lundgren, M. & Jörnsten, K. & Rönnqvist, M., 2010. "Cost allocation in collaborative forest transportation," European Journal of Operational Research, Elsevier, vol. 205(2), pages 448-458, September.
    17. Lozano, S. & Moreno, P. & Adenso-Díaz, B. & Algaba, E., 2013. "Cooperative game theory approach to allocating benefits of horizontal cooperation," European Journal of Operational Research, Elsevier, vol. 229(2), pages 444-452.
    18. Naccache, Salma & Côté, Jean-François & Coelho, Leandro C., 2018. "The multi-pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 269(1), pages 353-362.
    19. Allahyari, Somayeh & Salari, Majid & Vigo, Daniele, 2015. "A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 756-768.
    20. Bektaş, Tolga & Gouveia, Luis & Martínez-Sykora, Antonio & Salazar-González, Juan-José, 2019. "Balanced vehicle routing: Polyhedral analysis and branch-and-cut algorithm," European Journal of Operational Research, Elsevier, vol. 273(2), pages 452-463.
    21. Mesa-Arango, Rodrigo & Ukkusuri, Satish V., 2015. "Demand clustering in freight logistics networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 36-51.
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