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Recent deep models for solving routing problems always assume a single distribution of nodes for training, which severely impairs their cross-distribution generalization ability.
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Machine learning for combinatorial optimization: a methodological tour d’horizon
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Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
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Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
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Learning Improvement Heuristics for Solving Routing Problems
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Does distributionally robust supervised learning give robust classifiers?
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