Are there research groups working on using deep learning for combinatorial optimization problems?


2 Answers 2


Yep, there's a paper Pointer Networks that tries to use deep learning to solve convex hull, Delaunay triangulation and TSP, the result looks promising, or at least it can be used as a good starting point for optimization algorithms.

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Machine learning can be used in the branch and bound algorithm to

  • Select a branching variable (Khalil, Elias Boutros, et al. "Learning to branch in mixed integer programming." Thirtieth AAAI Conference on Artificial Intelligence. 2016.)
  • Decide whether or not to run a primal heuristic at a node (Khalil, Elias B., et al. "Learning to Run Heuristics in Tree Search." IJCAI. 2017.)

Reinforcement learning can be used to

  • Learn a better criterion for greedy solution construction over a graph distribution (Khalil, Elias, et al. "Learning combinatorial optimization algorithms over graphs." Advances in Neural Information Processing Systems. 2017.)

Check Bistra Dilkina's (who seems to pioneered this approach) talk at USC ISI AI seminar.


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