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Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap

Author

Listed:
  • Md. Anisul Islam

    (Department of Mechanical Engineering, Room E2-327, EITC Building, University of Manitoba, Winnipeg, MB R3T 5V6, Canada)

  • Yuvraj Gajpal

    (Department of Supply Chain Management, 631-181 Freedman Crescent, Asper School of Business, University of Manitoba, Winnipeg, MB R3T 5V4, Canada)

Abstract

The CO 2 emission of transportation is significantly reduced by the employment of green vehicles to the existing vehicle fleet of the organizations. This paper intends to optimize the composition of conventional and green vehicles for a logistics distribution problem operating under a carbon emission cap imposed by the government. The underlying problem involves product delivery by the vehicles starting from a single depot to geographically distributed customers. The delivery occurs within specified time windows. To solve the proposed problem, we design a hybrid metaheuristic solution based on ant colony optimization (ACO) and variable neighborhood search (VNS) algorithms. Extensive computational experiments have been performed on newly generated problem instances and benchmark problem instances adopted from the literature. The proposed hybrid ACO is proven to be superior to the state-of-the-art algorithms available in the literature. We obtain 21 new best-known solutions out of 56 benchmark instances of vehicle routing problem with time windows (VRPTW). The proposed mixed fleet model obtains the best composition of conventional and green vehicles with a 6.90% reduced amount of CO 2 emissions compared to the case when the fleet consists of conventional vehicles only.

Suggested Citation

  • Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6940-:d:578495
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    References listed on IDEAS

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    2. Xiaohong Yin & Yufei Wu & Qiang Liu, 2023. "Dynamic Evaluation of Energy Carbon Efficiency in the Logistics Industry Based on Catastrophe Progression," Sustainability, MDPI, vol. 15(6), pages 1-17, March.

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