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Determination of green vehicle routing problem via differential evolution

Author

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  • Siwaporn Kunnapapdeelert
  • Ratchaphong Klinsrisuk

Abstract

This paper presents the comparison of pickup and delivery with time window (PDPTW) and green vehicle routing for pickup and delivery problems, with time windows (Green-PDPTW) by using differential evolution (DE) algorithm. The main idea of PDPTW is to design the optimal route for transportation by minimising the total cost. Green-PDPTW aims to design the route by minimising the emission of direct greenhouse gases, i.e., carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). These two concepts were verified by eight standard benchmark instances. DE algorithm is proposed to design the optimal route for these two problems. The computational experiments demonstrate that designing route by minimising greenhouse gases emission provides cleaner routes than designing routes by minimising total cost. However, it is not as economical as considering the minimum total cost as the objective function since it requires more vehicles and total distance than route that designed based on the minimum total cost concept.

Suggested Citation

  • Siwaporn Kunnapapdeelert & Ratchaphong Klinsrisuk, 2019. "Determination of green vehicle routing problem via differential evolution," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 34(3), pages 395-410.
    • Handle: RePEc:ids:ijlsma:v:34:y:2019:i:3:p:395-410
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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. 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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