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Multiobjective Vehicle Routing Problem with Route Balance Based on Genetic Algorithm

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Listed:
  • Wei Zhou
  • Tingxin Song
  • Fei He
  • Xi Liu

Abstract

This study proposes a genetic algorithm to solve the biobjective vehicle routing problem with time windows simultaneously considering total distance and distance balance of active vehicle fleet. A new complex chromosome is used to present the active vehicle route. Through tournament selection, one-point crossover, and migrating mutation operator, the solution of the problem is solved. In experiment on Solomon’s benchmark problems, considering the total distance and distance balance, the results are improved in all classes of problems. According to the experimental results, the suggested approach is sufficient and the average GA performance is good.

Suggested Citation

  • Wei Zhou & Tingxin Song & Fei He & Xi Liu, 2013. "Multiobjective Vehicle Routing Problem with Route Balance Based on Genetic Algorithm," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-9, December.
    • Handle: RePEc:hin:jnddns:325686
    DOI: 10.1155/2013/325686
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    Cited by:

    1. Zelda B. Zabinsky & Pattamon Dulyakupt & Shabnam Zangeneh-Khamooshi & Cao Xiao & Pengbo Zhang & Seksan Kiatsupaibul & Joseph A. Heim, 2020. "Optimal collection of medical specimens and delivery to central laboratory," Annals of Operations Research, Springer, vol. 287(1), pages 537-564, April.
    2. Rodrigo Linfati & Fernando Yáñez-Concha & John Willmer Escobar, 2022. "Mathematical Models for the Vehicle Routing Problem by Considering Balancing Load and Customer Compactness," Sustainability, MDPI, vol. 14(19), pages 1-20, October.

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