Machine Learning for K-Adaptability in Two-Stage Robust Optimization
Published Online:2 Sep 2024https://doi.org/10.1287/ijoc.2022.0314
References
- (2021) Machine learning for combinatorial optimization: A methodological tour d’horizon. Eur. J. Oper. Res. 290(2):405–421.Crossref, Google Scholar
- (2009) Robust Optimization, vol. 28 (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
- (2004) Adjustable robust solutions of uncertain linear programs. Math. Programming 99(2):351–376.Crossref, Google Scholar
- (2010) Finite adaptability in multistage linear optimization. IEEE Trans. Automatic Control 55(12):2751–2766.Crossref, Google Scholar
- (2016) Multistage robust mixed-integer optimization with adaptive partitions. Oper. Res. 64(4):980–998.Link, Google Scholar
- (2012) A survey of Monte Carlo tree search methods. IEEE Trans. Comput. Intelligence AI Games 4(1):1–43.Crossref, Google Scholar
- (2023) A double-oracle, logic-based benders decomposition approach to solve the K-adaptability problem. Comput. Oper. Res. 155(2023):106243.Crossref, Google Scholar
- Gurobi Optimization LLC (2020) Gurobi optimizer reference manual. Accessed November 19, 2022, http://www.gurobi.com.Google Scholar
- (2002) Uncertainty-immunized solutions in linear programming. Master’s thesis, Technion, Israeli Institute of Technology, Haifa.Google Scholar
- (2015) K-adaptability in two-stage robust binary programming. Oper. Res. 63(4):877–891.Link, Google Scholar
- (2014) Learning to search in branch and bound algorithms. Adv. Neural Inform. Processing Systems 27(2014):3293–3301.Google Scholar
- (2024) Machine learning for K-adaptability in two-stage robust optimization. http://dx.doi.org/10.1287/ijoc.2022.0314.cd, https://github.com/INFORMSJoC/2022.0314.Google Scholar
- (2022a) MIP-GNN: A data-driven framework for guiding combinatorial solvers. Proc. Conf. AAAI Artificial Intelligence 36(9):10219–10227.Crossref, Google Scholar
- (2022b) Finding backdoors to integer programs: A Monte Carlo tree search framework. Proc. Conf. AAAI Artificial Intelligence 36(4):3786–3795.Crossref, Google Scholar
- (2013) Bandit-based search for constraint programming. Principles Practice Constraint Programming, 19th Internat. Conf., CP 2013 (Springer, Berlin, Heidelberg), 464–480.Google Scholar
- (2011) Scikit-learn: Machine learning in Python. J. Machine Learn. Res. 12(85):2825–2830.Google Scholar
- (2016) Multistage adjustable robust mixed-integer optimization via iterative splitting of the uncertainty set. INFORMS J. Comput. 28(3):553–574.Link, Google Scholar
- (2012) Guiding combinatorial optimization with UCT. Integration AI OR Techniques Constraint Programming Combinatorial Optimization Problems, 9th Internat. Conf., CPAIOR 2012 (Springer, Berlin, Heidelberg), 356–361.Google Scholar
- (2020) K-adaptability in two-stage mixed-integer robust optimization. Math. Programming Comput. 12(2):193–224.Crossref, Google Scholar
- (2023) Monte Carlo tree search: A review of recent modifications and applications. Artificial Intelligence Rev. 56(2023):2497–2562.Crossref, Google Scholar

