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The NR-EGA for the EVRP Problem with the Electric Energy Consumption Model

Author

Listed:
  • Yanfei Zhu

    (School of Automation, Guangdong University of Technology, Guangzhou 510006, China)

  • Chunhui Li

    (School of Automation, Guangdong University of Technology, Guangzhou 510006, China)

  • Kwang Y. Lee

    (Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA)

Abstract
Nowadays, in researches on electric vehicle routing problems, in order to improve the delivery efficiency and reduce the routing cost, many important elements are broad discussed such as the customer time window, the routing algorithm, the electric energy consumption, etc. In these, the routing algorithm is the key element to achieve a good solution. Based on this background, the paper investigates the routing algorithm, then adopts the elitist genetic algorithm and proposes an improved neighbor routing initialization method for solving the electric vehicle routing problem. In our method, the electric vehicle energy consumption is used as the main component of the routing system. The neighbor routing initialization enables the routing system to choose the close route from a suitable first customer in the initialization, which makes the routing search faster and find the global optimal route easily. The simulations on the Solomon benchmark data and the Hiland Dairy milk delivery example in Dallas, Texas, USA verifies the good performance of the method.

Suggested Citation

  • Yanfei Zhu & Chunhui Li & Kwang Y. Lee, 2022. "The NR-EGA for the EVRP Problem with the Electric Energy Consumption Model," Energies, MDPI, vol. 15(10), pages 1-12, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3681-:d:817889
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    References listed on IDEAS

    as
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