Attention, Learn to Solve Routing Problems!
Abstract
Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.
The recently presented idea to learn heuristics for combinatorial optimization problems is promising as it can save costly development. However, to push this idea towards practical implementation, we need better models and better ways of training. We contribute in both directions: we propose a model based on attention layers with benefits over the Pointer Network and we show how to train this model using REINFORCE with a simple baseline based on a deterministic greedy rollout, which we find is more efficient than using a value function. We significantly improve over recent learned heuristics for the Travelling Salesman Problem (TSP), getting close to optimal results for problems up to 100 nodes. With the same hyperparameters, we learn strong heuristics for two variants of the Vehicle Routing Problem (VRP), the Orienteering Problem (OP) and (a stochastic variant of) the Prize Collecting TSP (PCTSP), outperforming a wide range of baselines and getting results close to highly optimized and specialized algorithms.
Results and benchmarks
The recently presented idea to learn heuristics for combinatorial optimization problems is promising as it can save costly development.
Benchmark evidence is limited
Evidence graph: 3 refs, 3 links.
Utility signals: depth 70/100, grounding 75/100, status medium.
Implementation
No direct implementation yet
Maintained implementation evidence is not confirmed for this paper yet.
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Time to first repro: a few days
JaswanthBadvelu/Reinforcement-Learning-CVRP is the closest maintained adjacent implementation (Matches contextual method/domain keyword: heuristics). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 50 GitHub stars.
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Reproduction readiness
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Hardware requirements
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Validation caveat
Framework baselines
- Hugging Face Transformers training guide
Modern transformer training baseline.
- PyTorch nn.Transformer docs
Reference transformer building block implementation.
Repositories and ecosystem
Closest related implementations
These are not paper-verified. Use them as reference points when no direct implementation is available.
- JaswanthBadvelu/Reinforcement-Learning-CVRP Adjacent · Confidence: Low · 50 stars
Matches contextual method/domain keyword: heuristics
No additional verified repositories beyond the primary recommendation.
Hugging Face artifacts
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Research context
192
Citations
0
References
Tasks
Orienteering, Heuristics, Computer science, Hyperparameter, Travelling salesman problem, Vehicle routing problem, Pointer (user interface), Range (aeronautics)
Methods
Mathematical optimization, Greedy algorithm, Combinatorial optimization
Domains
Artificial intelligence
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