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Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems
The application of learning based methods to vehicle routing problems has emerged as a pivotal area of research in combinatorial optimization. These problems are characterized by vast solution spaces and intricate constraints, making traditional approaches such as exact mathematical models or heuris
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