Abstract
For the first time, a fully neural approach has been proposed, capable of solving the optimization problem of routes of extremely large dimensions (~5000 points) with real-world constraints such as cargo capacity, time windows, and delivery sequencing. The proposed solution allows for rapid suboptimal problem solving for small and medium dimensions (<1000 points). Meanwhile, it outperforms heuristic approaches for tasks of extremely large dimensions (>1000 points), thereby representing a state-of-the-art (SotA) solution in the field of route optimization with real-world constraints and extremely large dimensions.
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Soroka, A.G., Meshcheryakov, A.V. Solving Large-Scale Routing Optimization Problems with Networks and Only Networks. Dokl. Math. 108 (Suppl 2), S242–S247 (2023). https://doi.org/10.1134/S1064562423701119
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DOI: https://doi.org/10.1134/S1064562423701119