AI RESEARCH
NCO4CVRP: Neural Combinatorial Optimization for the Capacitated Vehicle Routing Problem
arXiv CS.LG
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ArXi:2604.16581v1 Announce Type: new Neural Combinatorial Optimization (NCO) has emerged as a powerful framework for solving combinatorial optimization problems by integrating deep learning-based models. This work focuses on improving existing inference techniques to enhance solution quality and generalization. Specifically, we modify the Random Re-Construct (RRC) approach of the Light Encoder Heavy Decoder (LEHD) model by incorporating Simulated Annealing (SA). Unlike the conventional RRC, which greedily replaces suboptimal segments, our SA-based modification.