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Routing problems, like the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP), are NP-hard and slow to solve for large instances. Diffusion-based solvers can be trained in a supervised way using sets of optimal solutions, and then quickly solve new test instances. However, for large ins...
The COMPASS algorithm for OCTSP is introduced, which combines search with learning-accelerated routing by orchestrating parallel sub-solvers and can reach exact solutions in time exponential in cluster size rather than instance size.
This work introduces an optimization framework where a reinforcement learning agent is trained on prior instances and quickly generates initial solutions, which are then further optimized by a genetic algorithm, enabling real-time and interactive routing at scale.
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