Neural Combinatorial Optimization with Attention Models

My core research interest is Neural Combinatorial Optimization (NCO): training deep neural networks to solve classic combinatorial optimization problems such as the Travelling Salesman Problem (TSP), Capacitated Vehicle Routing (CVRP), scheduling, and assignment. I focus on attention-based encoder–decoder architectures, Pointer Networks, and graph neural networks that learn to construct high-quality solutions directly from data, complementing or replacing hand-crafted heuristics.