Hybrid genetic algorithm for solving an online vehicle routing problem with time windows and heterogeneous fleet

Informations générales

Année de publication

2024

Type

Conférence

Description

23rd International Conference on Hybrid Intelligent Systems (HIS'23), 437-446, Springer Nature Switzerland

Résumé

The Vehicle Routing Problem (VRP) is a well-known optimization problem in which we aim traditionally to minimize transportation costs while satisfying customer demands. In fact, most logistics companies use a heterogeneous fleet with varying capacities and costs, presenting a more complex variant known as Rich VRP (RVRP). In this paper, we present a mathematical formulation of the RVRP, considering both hard time windows and dynamically changing requests to be as close as possible to real-life logistics scenarios. To solve this challenging problem, we propose a Hybrid Genetic Algorithm (HGA). The experimental study highlights the out-performance of our proposal when evaluated alongside other algorithms on the same benchmark problems. Additionally, we conduct a sensitivity analysis to illustrate how resilient the algorithm is when problem parameters are altered.

BibTeX
@inproceedings{labidi2023hybrid,
  title={Hybrid Genetic Algorithm for Solving an Online Vehicle Routing Problem with Time Windows and Heterogeneous Fleet},
  author={Labidi, Hamida and Chaabani, Abir and Azzouna, Nadia Ben and Hassine, Khaled},
  booktitle={International Conference on Hybrid Intelligent Systems},
  pages={437--446},
  year={2023},
  organization={Springer}
}

Auteurs

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