mlsanityData to 7 Oct 2026

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

arXiv 2309.14032 ↗First posted 25 Sep 2023cs.NE cs.AI cs.LGcited by 77

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Abstract (arXiv)

Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO for a specific problem requires the expert design of knowledge-driven heuristics. In this paper, we propose DeepACO, a generic framework that leverages deep reinforcement learning to automate heuristic designs. DeepACO serves to strengthen the heuristic measures of existing ACO algorithms and dispense with laborious manual design in future ACO applications. As a neural-enhanced meta-heuristic, DeepACO consistently outperforms its ACO counterparts on eight COPs using a single neural architecture and a single set of hyperparameters. As a Neural Combinatorial Optimization method, DeepACO performs better than or on par with problem-specific methods on canonical routing problems. Our code is publicly available at https://github.com/henry-yeh/DeepACO.

Key facts. Cited by 77 papers in the map (data through 7 Oct 2026). Builds on 50 of its 95 references that are in the map. First posted on arXiv 25 Sep 2023.

Builds on

50 of 95 references.

References · 50

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38 more
  1. 2020POMO: Policy Optimization with Multiple Optima for Reinforcement Learningcited by 341
  2. 2018Reinforcement Learning for Solving the Vehicle Routing Problemcited by 327
  3. 2019An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problemcited by 265
  4. 2020Reinforcement Learning for Combinatorial Optimization: A Surveycited by 235
  5. 2023DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimizationcited by 216
  6. 2018Learning to Perform Local Rewriting for Combinatorial Optimizationcited by 183
  7. 2019Learning Improvement Heuristics for Solving Routing Problemscited by 162
  8. 2020Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instancescited by 161
  9. 2022DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problemscited by 127
  10. 2020Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhoodcited by 122
  11. 2022Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimizationcited by 118
  12. 2021Learning to Delegate for Large-scale Vehicle Routingcited by 108
  13. 2021Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformercited by 108
  14. 2021NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problemcited by 102
  15. 2020Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learningcited by 100
  16. 2020Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problemscited by 100
  17. 2021Efficient Active Search for Combinatorial Optimization Problemscited by 99
  18. 2020Learning the Travelling Salesperson Problem Requires Rethinking Generalizationcited by 96
  19. 2021Deep Policy Dynamic Programming for Vehicle Routing Problemscited by 94
  20. 2021Learning Collaborative Policies to Solve NP-hard Routing Problemscited by 86
  21. 2022Simulation-guided Beam Search for Neural Combinatorial Optimizationcited by 84
  22. 2021Graph Neural Network Guided Local Search for the Traveling Salesperson Problemcited by 70
  23. 2023RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmarkcited by 70
  24. 2022Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillationcited by 61
  25. 2021The Transformer Network for the Traveling Salesman Problemcited by 59
  26. 2023Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problemcited by 49
  27. 2021Learning to Schedule Heuristics in Branch-and-Boundcited by 45
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  33. 2023Neural Airport Ground Handlingcited by 7
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  35. 2022Improving Ant Colony Optimization Efficiency for Solving Large TSP Instancescited by 6
  36. 2022Neural Combinatorial Optimization: a New Player in the Fieldcited by 6
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  38. 2020A Weighted Population Update Rule for PACO Applied to the Single Machine Total Weighted Tardiness Problemcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 22; 2025: 36; 2026: 18.

77 papers.

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  1. 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolutioncited by 266
  2. 2024MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Expertscited by 69
  3. 2024RouteFinder: Towards Foundation Models for Vehicle Routing Problemscited by 54
  4. 2024Ant Colony Sampling with GFlowNets for Combinatorial Optimizationcited by 53
  5. 2025Rethinking Light Decoder-based Solvers for Vehicle Routing Problemscited by 36
  6. 2024Learning to Handle Complex Constraints for Vehicle Routing Problemscited by 29
  7. 2025Large Language Models as End-to-end Combinatorial Optimization Solverscited by 27
  8. 2024Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithmscited by 23
  9. 2024Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectivescited by 23
  10. 2025Neural Deconstruction Search for Vehicle Routing Problemscited by 15
  11. 2025Preference Optimization for Combinatorial Optimization Problemscited by 11
  12. 2024DISCO: Efficient Diffusion Solver for Large-Scale Combinatorial Optimization Problemscited by 10
38 more
  1. 2025Adversarial Generative Flow Network for Solving Vehicle Routing Problemscited by 10
  2. 2025RRNCO: Towards Real-World Routing with Neural Combinatorial Optimizationcited by 10
  3. 2025FrontierCO: Real-World and Large-Scale Evaluation of Machine Learning Solvers for Combinatorial Optimizationcited by 10
  4. 2024Collaboration! Towards Robust Neural Methods for Routing Problemscited by 9
  5. 2024Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimizationcited by 8
  6. 2024LLMs for Cold-Start Cutting Plane Separator Configurationcited by 8
  7. 2024Ensembling Prioritized Hybrid Policies for Multi-agent Pathfindingcited by 7
  8. 2024PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimizationcited by 7
  9. 2025Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Schedulingcited by 7
  10. 2025Generalizable Heuristic Generation Through LLMs with Meta-Optimizationcited by 7
  11. 2025URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalizationcited by 7
  12. 2025Hybrid-Balance GFlowNet for Solving Vehicle Routing Problemscited by 7
  13. 2024Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and Morecited by 6
  14. 2025Learning for routing: A guided review of recent developments and future directionscited by 6
  15. 2025VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problemscited by 6
  16. 2024Moco: A Learnable Meta Optimizer for Combinatorial Optimizationcited by 5
  17. 2024Neural Solver Selection for Combinatorial Optimizationcited by 5
  18. 2025Neural Genetic Search in Discrete Spacescited by 5
  19. 2025Learning to Segment for Vehicle Routing Problemscited by 5
  20. 2026PathWise: Planning through World Model for Automated Heuristic Design via Self-Evolving LLMscited by 5
  21. 2024A Unified Framework for Combinatorial Optimization Based on Graph Neural Networkscited by 4
  22. 2024Memory-Enhanced Neural Solvers for Routing Problemscited by 4
  23. 2025RedAHD: Reduction-Based End-to-End Automatic Heuristic Design with Large Language Modelscited by 4
  24. 2026Survey on Neural Routing Solverscited by 4
  25. 2024Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learningcited by 3
  26. 2024MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimizationcited by 3
  27. 2025Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLMcited by 3
  28. 2025Probing Neural Combinatorial Optimization Modelscited by 3
  29. 2026TIDE: Tuning-Integrated Dynamic Evolution for LLM-Based Automated Heuristic Designcited by 3
  30. 2023An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problemscited by 2
  31. 2025Pheromone-based Learning of Optimal Reasoning Pathscited by 2
  32. 2025Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Setcited by 2
  33. 2025Accelerating Vehicle Routing via AI-Initialized Genetic Algorithmscited by 2
  34. 2026RefineEvo: Planning-Guided Heuristic Evolution with Bidirectional Experiencecited by 2
  35. 2024On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problemcited by 1
  36. 2025USPR: Learning a Unified Solver for Profiled Routingcited by 1
  37. 2025Multimodal Fused Learning for Solving the Generalized Traveling Salesman Problem in Robotic Task Planningcited by 1
  38. 2025ViTSP: A Vision Language Models Guided Framework for Solving Large-Scale Traveling Salesman Problemscited by 1

50 most cited of 77 All 77 (JSON)