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Smart routes: a system for development and comparison of algorithms for solving vehicle routing problems with realistic constraints — arXiv:2608.14140

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.14140
License (as archived): CC0-1.0
Archived: 2026-10-19T02:30:34.794Z
SHA-256 of the archived text: a38aa3047110630f7b1c43da8a795da2f0064445337fb5ba66dbea3cc5a62f4e
Stable URL of this page: https://metraipolis.com/documento/dc_c8f596f41dcc

How to cite

Smart routes: a system for development and comparison of algorithms for solving vehicle routing problems with realistic constraints — arXiv:2608.14140 — arXiv (en), https://arxiv.org/abs/2608.14140 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_c8f596f41dcc (Metraipolis archive dc_c8f596f41dcc, sha256 a38aa3047110630f7b1c43da8a795da2f0064445337fb5ba66dbea3cc5a62f4e)

BibTeX

@misc{dcc8f596f41dcc,
  title = {Smart routes: a system for development and comparison of algorithms for solving vehicle routing problems with realistic constraints — arXiv:2608.14140},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.14140},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_c8f596f41dcc; sha256 a38aa3047110630f7b1c43da8a795da2f0064445337fb5ba66dbea3cc5a62f4e},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.14140. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

The problem of route optimization with realistic constraints is becoming extremely relevant in the face of global urban population growth. While we are aware of approaches that theoretically provide an exact optimal solution, their application becomes challenging as the problem size increases because of exponential complexity. We investigate the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) and compare solutions obtaining by exact solver SCIP with heuristic algorithms such as LKH, 2-OPT, 3-OPT, the ORTools framework, and the deep learning model JAMPR. We demonstrate that for problem of size 50 deep learning and classical heuristic solutions became close to SCIP exact solution but requires less time. Additionally for problems with size 100, SCIP exact methods around 13 times slower that neural and classical heuristics with the same route cost and on around 50% worse for the first feasible solution on the same time. To conduct experiments, we developed the Smart Routes platform for solving route optimization problems, which includes exact, heuristic, and deep learning models, and facilitates convenient integration of custom algorithms and datasets.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-17 in cs.LG).
Categorie arXiv: Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2608.14140 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T02:26:17.793Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-08-17?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).