Geometry-Aware Reinforcement Learning for 2D Irregular Nesting
This paper introduces the Polygons Transformer (PoT), a novel architecture that encodes 2D continuous vector geometries while allowing cross-polygon attention and couple this novel architecture with a Combinatorial Optimization Reinforcement Learning (CORL) training framework to find optimal solutions.