Solving Large-Scale Routing Optimization Problems with Networks and Only Networks

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), thereby representing a state-of-the-art (SotA) solution in the field of route optimization with real-world constraints and extremely large dimensions.