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Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm

Author

Listed:
  • Bo Peng

    (School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China)

  • Lifan Wu

    (School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China)

  • Yuxin Yi

    (College of Management, Sichuan Agricultural University, Chengdu 610074, China)

  • Xiding Chen

    (Department of Finance, Wenzhou Business College, Wenzhou 325035, China)

Abstract

The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.

Suggested Citation

  • Bo Peng & Lifan Wu & Yuxin Yi & Xiding Chen, 2020. "Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2127-:d:330461
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    References listed on IDEAS

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