Abstract
We propose a new approach for search tree exploration in the context of combinatorial optimization, specifically Mixed Integer Programming (MIP), that is based on UCT, an algorithm for the multi-armed bandit problem designed for balancing exploration and exploitation in an online fashion. UCT has recently been highly successful in game tree search. We discuss the differences that arise when UCT is applied to search trees as opposed to bandits or game trees, and provide initial results demonstrating that the performance of even a highly optimized state-of-the-art MIP solver such as CPLEX can be boosted using UCT’s guidance on a range of problem instances.
A preliminary version of this paper appeared at the Workshop on Monte-Carlo Tree Search held in Freiburg, Germany in June 2011. The current implementation relies on a newer version of the CPLEX solver, capitalizing on additional cuts learned during search and resulting in significantly improved performance.
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Sabharwal, A., Samulowitz, H., Reddy, C. (2012). Guiding Combinatorial Optimization with UCT. In: Beldiceanu, N., Jussien, N., Pinson, É. (eds) Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems. CPAIOR 2012. Lecture Notes in Computer Science, vol 7298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29828-8_23
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DOI: https://doi.org/10.1007/978-3-642-29828-8_23
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