In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted at the Data Science meets Optimization workshop at IJCAI21 and consists of two tracks:

• Online supervised learning using surrogate models
• Reinforcement learning

The goal of this competition is to strengthen the relation between the machine learning field and the optimization field. You can learn more about the competition here.

Cash prizes will be announced soon!

• May 7: Start of the tryout period
• May 21: Competition start
• July 5: Submission deadline (validation)
• July 12: Submission deadline (test)
• August 9: Winners are contacted privately
• August 21/22: Public announcement of winners

For more details about the competition, please refer to this document.

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• Python=3.8 (should be OK with v >= 3.6)
• PyTorch=1.8 (track 2 only)
• Numpy=1.20
• bayesian-optimization=1.1.0 (track 1 only)
• Pandas=1.2.4
• Conda=4.8.4 (optional)

Please check environment.yml

Special thanks to https://github.com/pemami4911/neural-combinatorial-rl-pytorch for the implemetation of Neural CO used as part of this repository.