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Multi-depot Two-Echelon Fuel Minimizing Routing Problem with Heterogeneous Fleets: Model and Heuristic

Author

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  • Surendra Reddy Kancharla

    (Indian Institute of Technology Madras)

  • Gitakrishnan Ramadurai

    (Indian Institute of Technology Madras)

Abstract

We formulate the two-echelon routing problem considering multiple depots and heterogeneous fleets. Our study (a) presents a Mixed Integer Linear Programming (MILP) formulation with load-dependent fuel minimization objective, (b) uses driving cycles to represent speed variations along a path, (c) allows the vehicles to return to any depot/satellite, and (d) conserves the total number of vehicles at each depot/satellite. We call the problem a Multi-Depot Two-Echelon Fuel Minimizing Routing Problem (MD2E-FMRP). Prior studies assumed there is a fixed number of vehicles available at each satellite/depot, whereas we allow different number of vehicles of each vehicle type at each satellite and depot. Our formulation relaxes several unrealistic assumptions in existing two-echelon formulations and hence has greater practical application. Despite the relaxation of constraints, the running time of our model is comparable to existing formulations. Gurobi optimizer is used to find a better upper bound for up to 56 node instances within a given time limit of 10,000s. We also propose an Adaptive Large Neighborhood Search (ALNS) based heuristic solution technique that outperformed Gurobi in all the tested instances of MD2E-FMRP. We observe an average saving of 13.11% in fuel consumption by minimizing fuel consumed instead of minimizing distance. In general, adapting heterogeneous fleets results in fuel savings and consequently lower emissions compared to using a homogeneous fleet.

Suggested Citation

  • Surendra Reddy Kancharla & Gitakrishnan Ramadurai, 2019. "Multi-depot Two-Echelon Fuel Minimizing Routing Problem with Heterogeneous Fleets: Model and Heuristic," Networks and Spatial Economics, Springer, vol. 19(3), pages 969-1005, September.
    • Handle: RePEc:kap:netspa:v:19:y:2019:i:3:d:10.1007_s11067-018-9437-7
    DOI: 10.1007/s11067-018-9437-7
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    Cited by:

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    2. Qiu, Rui & Xu, Jiuping & Ke, Ruimin & Zeng, Ziqiang & Wang, Yinhai, 2020. "Carbon pricing initiatives-based bi-level pollution routing problem," European Journal of Operational Research, Elsevier, vol. 286(1), pages 203-217.
    3. Sluijk, Natasja & Florio, Alexandre M. & Kinable, Joris & Dellaert, Nico & Van Woensel, Tom, 2023. "Two-echelon vehicle routing problems: A literature review," European Journal of Operational Research, Elsevier, vol. 304(3), pages 865-886.
    4. Yue Lu & Maoxiang Lang & Xueqiao Yu & Shiqi Li, 2019. "A Sustainable Multimodal Transport System: The Two-Echelon Location-Routing Problem with Consolidation in the Euro–China Expressway," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    5. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    6. Li, Hongqi & Wang, Haotian & Chen, Jun & Bai, Ming, 2021. "Two-echelon vehicle routing problem with satellite bi-synchronization," European Journal of Operational Research, Elsevier, vol. 288(3), pages 775-793.
    7. Erfan Babaee Tirkolaee & Alireza Goli & Abbas Mardani, 2023. "A novel two-echelon hierarchical location-allocation-routing optimization for green energy-efficient logistics systems," Annals of Operations Research, Springer, vol. 324(1), pages 795-823, May.

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