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Dynamic graph Conv-LSTM model with dynamic positional encoding for the large-scale traveling salesman problem
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4615-3618-5_2openalex-snapshot
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
inferredcites →https://doi.org/10.1007/978-3-031-08011-1_14openalex-snapshot
Deep Policy Dynamic Programming for Vehicle Routing Problems
inferredcites →https://doi.org/10.1007/978-3-642-51565-1openalex-snapshot
Mathematical Models in Marketing
inferredcites →https://doi.org/10.1007/bf00339943openalex-snapshot
“Neural” computation of decisions in optimization problems
inferredcites →https://doi.org/10.1016/0304-3975(77)90012-3openalex-snapshot
The Euclidean travelling salesman problem is NP-complete
inferredcites →https://doi.org/10.1016/j.ejor.2020.07.063openalex-snapshot
Machine learning for combinatorial optimization: A methodological tour d’horizon
inferredcites →https://doi.org/10.1016/j.jocs.2021.101454openalex-snapshot
Transformation operators based grey wolf optimizer for travelling salesman problem
inferredcites →https://doi.org/10.1016/j.knosys.2021.107526openalex-snapshot
Deep reinforcement learning for transportation network combinatorial optimization: A survey
inferredcites →https://doi.org/10.1016/j.orl.2008.09.006openalex-snapshot
Certification of an optimal TSP tour through 85,900 cities
inferredcites →https://doi.org/10.1109/tnnls.2020.2978386openalex-snapshot
A Comprehensive Survey on Graph Neural Networks
inferredcites →https://doi.org/10.1109/tnnls.2021.3068828openalex-snapshot
Learning Improvement Heuristics for Solving Routing Problems
inferredcites →https://doi.org/10.1145/321105.321111openalex-snapshot
Dynamic Programming Treatment of the Travelling Salesman Problem
inferredcites →https://doi.org/10.1155/2021/6645214openalex-snapshot
A Deep Learning Model with Conv-LSTM Networks for Subway Passenger Congestion Delay Prediction
inferredcites →https://doi.org/10.1287/ijoc.3.4.376openalex-snapshot
TSPLIB—A Traveling Salesman Problem Library
inferredcites →https://doi.org/10.1609/aaai.v35i13.17430openalex-snapshot
Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems
inferredcites →https://doi.org/10.17863/cam.85173openalex-snapshot
Learning the Travelling Salesperson Problem Requires Rethinking Generalization
inferredcites →https://doi.org/10.3934/mbe.2022158openalex-snapshot
Solving the TSP by the AALHNN algorithm
inferredcites →https://doi.org/10.48550/arxiv.1911.04936openalex-snapshot
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4666187openalex-extracted
Optimizing Decisions in Vehicle Routing Problems Using Deep Reinforcement Learning: Overview And Systematic Review
inferred← citeshttps://doi.org/10.1007/s00521-023-09042-6openalex-snapshot
NeuralGLS: learning to guide local search with graph convolutional network for the traveling salesman problem
inferred← citeshttps://doi.org/10.1007/s10462-025-11267-xopenalex-snapshot
Solving the traveling salesman problem with machine learning: a review of recent advances and challenges
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Air target intent recognition method combining graphing time series and diffusion models
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Harnessing the Power of Attention for Patch-Based Biomedical Image Classification
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Deep Reinforcement Learning Using Graph Conv-LSTM for Solving Multi-Objective Combinatorial Optimization Problems
inferred← citeshttps://doi.org/10.1109/conit69683.2026.11620624openalex-snapshot
Hybrid Reinforcement Learning Algorithm for Solving the Traveling Salesman Problem Using Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.1109/cscwd57460.2023.10152696openalex-snapshot
A Reinforcement Learning-driven Iterated Greedy Algorithm for Traveling Salesman Problem
inferred← citeshttps://doi.org/10.1109/icnlp60986.2024.10692972openalex-snapshot
AdHierNet: Enhancing Adversarial Robustness and Interpretability in Text Classification
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Design and Application of Artificial Intelligence Technology-Driven Education and Teaching System in Universities
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A Dual Long Short-Term Memory Model in Forecasting the Number of COVID-19 Infections
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A Hybrid Model Based on Improved Transformer and Graph Convolutional Network for COVID-19 Forecasting
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Integrating Transformer and GCN for COVID-19 Forecasting
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