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A green multi-depot location routing model with split-delivery and time window

Author

Listed:
  • Zahra Ebrahimi Qazvini
  • Mohsen Sadegh Amalnick
  • Hassan Mina

Abstract

Transportation imposes irreversible effects on the environment. Greenhouse gas emissions and carbon dioxide are either directly or indirectly associated with public health and ozone depletion. The necessity of addressing this issue emanates from the fact that, the greenhouse gases emitted by the transport sector comprise a significant portion of air pollution in many countries. Hence, the growing concern in this field has highlighted the need for the implementation of a comprehensive program to reduce the dangerous effects of road transport vehicles. To this end, green vehicle routing models based on lower fuel consumption and lower air pollution can be helpful. Therefore, in this study, a mixed integer linear model is presented for the so-called green routing problem. This is a multi-depot problem wherein the assumptions of time windows and split-delivery are considered. The results of the implementation of the model in a light auto parts distribution chain suggested the efficiency and effectiveness of the model.

Suggested Citation

  • Zahra Ebrahimi Qazvini & Mohsen Sadegh Amalnick & Hassan Mina, 2016. "A green multi-depot location routing model with split-delivery and time window," International Journal of Management Concepts and Philosophy, Inderscience Enterprises Ltd, vol. 9(4), pages 271-282.
    • Handle: RePEc:ids:ijmcph:v:9:y:2016:i:4:p:271-282
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    Citations

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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. Feiyue Qiu & Guodao Zhang & Ping-Kuo Chen & Cheng Wang & Yi Pan & Xin Sheng & Dewei Kong, 2020. "A Novel Multi-Objective Model for the Cold Chain Logistics Considering Multiple Effects," Sustainability, MDPI, vol. 12(19), pages 1-28, September.
    5. Longlong Leng & Yanwei Zhao & Jingling Zhang & Chunmiao Zhang, 2019. "An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem," IJERPH, MDPI, vol. 16(11), pages 1-28, June.
    6. 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.
    7. Garside, Annisa Kesy & Ahmad, Robiah & Muhtazaruddin, Mohd Nabil Bin, 2024. "A recent review of solution approaches for green vehicle routing problem and its variants," Operations Research Perspectives, Elsevier, vol. 12(C).

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