Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components

Anna Konovalenko, Lars Magnus Hvattum

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DOI: 10.3390/logistics8040096
Published: 10
Container: Logistics
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Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/logistics8040096,
  title = {Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components},
  author = {Anna Konovalenko and Lars Magnus Hvattum},
  year = {2024},
  journal = {Logistics},
  doi = {10.3390/logistics8040096},
  url = {https://doi.org/10.3390/logistics8040096}
}

RIS

TY  - JOUR
TI  - Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components
AU  - Anna Konovalenko
AU  - Lars Magnus Hvattum
PY  - 2024
JO  - Logistics
DO  - 10.3390/logistics8040096
UR  - https://doi.org/10.3390/logistics8040096
ER  -

APA

Konovalenko, A., & Hvattum, L. M. (2024). Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components. Logistics. https://doi.org/10.3390/logistics8040096

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doaj · retrieved 2026-09-25T07:59:16.796Z