Fetching the paper…
Reading the bibliography…
Mixed Integer Programming (MIP) solvers rely on an array of sophisticated heuristics developed with decades of research to solve large-scale MIP instances encountered in practice.
1901
Earlier work this paper cites.
1911
Earlier work this paper cites.
Land A, Doig A (1960) An automatic method of solving discrete programming problems. Econometrica 28(3):497–520
1960
Earlier work this paper cites.
Lawler EL, Wood DE (1966) Branch-and-bound methods: A survey. Operations research 14(4):699–719
1966
Earlier work this paper cites.
Karp RM (1972) Reducibility among combinatorial problems. Complexity of computer computations , 85–103 (Springer)
1972
Earlier work this paper cites.
Lions PL, Mercier B (1979) Splitting algorithms for the sum of two nonlinear operators. SIAM Journal on Numerical Analysis 16(6):964–979
1979
Earlier work this paper cites.
Pomerleau DA (1989) Alvinn: An autonomous land vehicle in a neural network. Advances in neural information processing systems , 305–313
1989
Earlier work this paper cites.
Eckstein J, Bertsekas DP (1992) On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators. Mathematical Programming 55(1-3):293–318
1992
Earlier work this paper cites.
Bain M, Sammut C (1995) A framework for behavioural cloning. Machine Intelligence 15 , 103–129
1995
Earlier work this paper cites.
Zhang W, Dietterich TG (1995) A reinforcement learning approach to job-shop scheduling. Proceedings of the 14th International Joint Conference on Artificial Intelligence - Volume 2 , 1114–1120, IJCAI’95 (San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.), ISBN 1558603638
1995
Earlier work this paper cites.
Boyan JA, Moore AW (1997) Using prediction to improve combinatorial optimization search. In Proc. of 6th Int’l Workshop on Artificial Intelligence and Statistics
1997
Earlier work this paper cites.
Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural computation 9(8):1735–1780
1997
Earlier work this paper cites.
Mladenović N, Hansen P (1997) Variable neighborhood search. Computers & operations research 24(11):1097–1100
1997
Earlier work this paper cites.
Dantzig GB (1998) Linear programming and extensions , volume 48 (Princeton university press)
1998
Earlier work this paper cites.
Shaw P (1998) Using constraint programming and local search methods to solve vehicle routing problems. International conference on principles and practice of constraint programming , 417–431 (Springer)
1998
Earlier work this paper cites.
Wolsey L (1998) Integer Programming . Wiley Series in Discrete Mathematics and Optimization (Wiley), ISBN 9780471283669, URL https://books.google.co.uk/books?id=x7RvQgAACAAJ
1998
Earlier work this paper cites.
Bengio Y, Bengio S (2000) Modeling high-dimensional discrete data with multi-layer neural networks. Solla S, Leen T, Müller K, eds., Advances in Neural Information Processing Systems , volume 12, 400–406 (MIT Press), URL https://proceedings.neurips.cc/paper/1999/file/e6384711491713d29bc63fc5eeb5ba4f-Paper.pdf
1999
Earlier work this paper cites.
Moll R, Barto AG, Perkins TJ, Sutton RS (1999) Learning instance-independent value functions to enhance local search. Kearns MJ, Solla SA, Cohn DA, eds., Advances in Neural Information Processing Systems 11 , 1017–1023 (MIT Press), URL http://papers.nips.cc/paper/1573-learning-instance-independent-value-functions-to-enhance-local-search.pdf
1999
Earlier work this paper cites.
2002
Earlier work this paper cites.
Achterberg T, Koch T, Martin A (2006) Miplib 2003. Operations Research Letters 34(4):361–372
2003
Earlier work this paper cites.
Boyd S, Vandenberghe L (2004) Convex optimization (Cambridge university press)
2004
Earlier work this paper cites.
2004
Earlier work this paper cites.
2004
Earlier work this paper cites.
Achterberg T, Koch T, Martin A (2005) Branching rules revisited. Operations Research Letters 33(1):42 – 54
2005
Earlier work this paper cites.
Berthold T (2006) Primal heuristics for mixed integer programs. URL https://opus4.kobv.de/opus4-zib/files/1029/Berthold_Primal_Heuristics_For_Mixed_Integer_Programs.pdf
2006
Earlier work this paper cites.
Bishop CM (2006) Pattern Recognition and Machine Learning (Information Science and Statistics) (Berlin, Heidelberg: Springer-Verlag), ISBN 0387310738, URL https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
2006
Earlier work this paper cites.
Berthold T (2007) Rens-relaxation enforced neighborhood search
2007
Earlier work this paper cites.
Conrad J, Gomes CP, van Hoeve WJ, Sabharwal A, Suter J (2007) Connections in networks: Hardness of feasibility versus optimality. Van Hentenryck P, Wolsey L, eds., Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems , 16–28 (Berlin, Heidelberg: Springer Berlin Heidelberg)
2007
Earlier work this paper cites.
Eckstein J, Nediak M (2007) Pivot, cut, and dive: A heuristic for 0-1 mixed integer programming. Journal of Heuristics 13(5):471–503
2007
Earlier work this paper cites.
Gomes CP, van Hoeve WJ, Sabharwal A (2008) Connections in networks: A hybrid approach. Perron L, Trick MA, eds., Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems , 303–307 (Berlin, Heidelberg: Springer Berlin Heidelberg)
2008
Earlier work this paper cites.
Jünger M, Liebling TM, Naddef D, Nemhauser GL, Pulleyblank WR, Reinelt G, Rinaldi G, Wolsey LA (2009) 50 Years of integer programming 1958-2008: From the early years to the state-of-the-art (Springer Science & Business Media)
2008
Earlier work this paper cites.
Achterberg T (2009) SCIP: solving constraint integer programs. Mathematical Programming Computation 1(1):1–41
2009
Cited alongside, same era.
Ansótegui C, Sellmann M, Tierney K (2009) A gender-based genetic algorithm for the automatic configuration of algorithms. Gent IP, ed., Principles and Practice of Constraint Programming - CP 2009 , 142–157 (Berlin, Heidelberg: Springer Berlin Heidelberg)
2009
Cited alongside, same era.
Hutter F, Hoos HH, Leyton-Brown K, Stützle T (2009) Paramils: An automatic algorithm configuration framework. J. Artif. Int. Res. 36(1):267–306, ISSN 1076-9757
2009
Cited alongside, same era.
Scarselli F, Gori M, Tsoi AC, Hagenbuchner M, Monfardini G (2009) The graph neural network model. IEEE Transactions on Neural Networks 20(1):61–80
2009
Cited alongside, same era.
Hansen P, Mladenović N, Pérez JAM (2010) Variable neighbourhood search: Methods and applications. Annals of Operations Research 175(1):367–407
Maher S, Miltenberger M, Pedroso JP, Rehfeldt D, Schwarz R, Serrano F (2016) PySCIPOpt: Mathematical programming in python with the SCIP optimization suite. Mathematical Software – ICMS 2016 , 301–307 (Springer International Publishing), URL http://dx.doi.org/10.1007/978-3-319-42432-3_37
2016
Later among the works it cites.
O’Donoghue B, Chu E, Parikh N, Boyd S (2016) Conic optimization via operator splitting and homogeneous self-dual embedding. Journal of Optimization Theory and Applications 169(3):1042–1068, URL http://stanford.edu/~boyd/papers/scs.html
2016
Later among the works it cites.
Cheng CH, Nührenberg G, Ruess H (2017) Maximum resilience of artificial neural networks. D’Souza D, Narayan Kumar K, eds., Automated Technology for Verification and Analysis , 251–268 (Springer International Publishing)
2017
Later among the works it cites.
Khalil EB, Dilkina B, Nemhauser GL, Ahmed S, Shao Y (2017b) Learning to run heuristics in tree search. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17 , 659–666, URL http://dx.doi.org/10.24963/ijcai.2017/92
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2010
Cited alongside, same era.
Shinano Y, Achterberg T, Berthold T, Heinz S, Koch T (2011) Parascip: a parallel extension of scip. Competence in High Performance Computing 2010 , 135–148 (Springer)
2010
Cited alongside, same era.
Boyd S, Parikh N, Chu E, Peleato B, Eckstein J (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine learning 3(1):1–122
2011
Cited alongside, same era.
Glankwamdee W, Linderoth JT (2011) Lookahead branching for mixed integer programming. ICS 2011
2011
Cited alongside, same era.
Hutter F, Hoos HH, Leyton-Brown K (2011) Sequential model-based optimization for general algorithm configuration. Proceedings of the 5th International Conference on Learning and Intelligent Optimization , 507–523, LION’05 (Springer-Verlag), ISBN 9783642255656
2011
Cited alongside, same era.
Ross S, Gordon G, Bagnell D (2011) A reduction of imitation learning and structured prediction to no-regret online learning. Proceedings of the fourteenth international conference on artificial intelligence and statistics , 627–635
2011
Cited alongside, same era.
Berthold T (2013) Measuring the impact of primal heuristics. Operations Research Letters 41(6):611–614
2013
Cited alongside, same era.
Domahidi A, Chu E, Boyd S (2013) ECOS: An SOCP solver for embedded systems. European Control Conference (ECC) , 3071–3076
2013
Cited alongside, same era.
2017
Later among the works it cites.
O’Neill R (2017) Computational issues in iso market models
2017
Later among the works it cites.
Schubert C (2017) Multi-level lookahead branching. Technical report, Institute of Mathematics, TU Berlin
2017
Later among the works it cites.
Balcan MF, Dick T, Sandholm T, Vitercik E (2018) Learning to branch. volume 80 of Proceedings of Machine Learning Research , 344–353 (Stockholmsmässan, Stockholm Sweden: PMLR), URL http://proceedings.mlr.press/v80/balcan18a.html
2018
Later among the works it cites.
2018
Later among the works it cites.
Bengio Y, Lodi A, Prouvost A (2018) Machine learning for combinatorial optimization: a methodological tour d’horizon
2018
Later among the works it cites.
Hendel G (2018) Adaptive large neighborhood search for mixed integer programming. Mathematical Programming Computation Under review
2018
Later among the works it cites.
Knueven B, Ostrowski J, Watson JP (2018) On mixed integer programming formulations for the unit commitment problem. Optimization Online Repository 2018, URL http://www.optimization-online.org/DB_FILE/2018/11/6930.pdf
2018
Later among the works it cites.
Li Z, Chen Q, Koltun V (2018) Combinatorial optimization with graph convolutional networks and guided tree search. Advances in Neural Information Processing Systems , 539–548
2018
Later among the works it cites.
Nazari M, Oroojlooy A, Snyder L, Takac M (2018) Reinforcement learning for solving the vehicle routing problem. Bengio S, Wallach H, Larochelle H, Grauman K, Cesa-Bianchi N, Garnett R, eds., Advances in Neural Information Processing Systems , volume 31, 9839–9849 (Curran Associates, Inc.), URL https://proceedings.neurips.cc/paper/2018/file/9fb4651c05b2ed70fba5afe0b039a550-Paper.pdf
2018
Later among the works it cites.
Xu K, Li C, Tian Y, Sonobe T, Kawarabayashi Ki, Jegelka S (2018) Representation learning on graphs with jumping knowledge networks. International Conference on Machine Learning
2018
Later among the works it cites.
Gasse M, Chételat D, Ferroni N, Charlin L, Lodi A (2019) Exact combinatorial optimization with graph convolutional neural networks. Advances in Neural Information Processing Systems , 15554–15566
2019
Later among the works it cites.
Gleixner A, Hendel G, Gamrath G, Achterberg T, Bastubbe M, Berthold T, Christophel PM, Jarck K, Koch T, Linderoth J, Lübbecke M, Mittelmann HD, Ozyurt D, Ralphs TK, Salvagnin D, Shinano Y (2019) MIPLIB 2017: Data-Driven Compilation of the 6th Mixed-Integer Programming Library. Technical report, Optimization Online, URL http://www.optimization-online.org/DB_FILE/2019/07/7285.html
2019
Later among the works it cites.
IBM ILOG CPLEX (2019) V12.10: User’s manual for CPLEX. URL https://www.ibm.com/analytics/cplex-optimizer
2019
Later among the works it cites.
Kool W, van Hoof H, Welling M (2019) Attention, learn to solve routing problems! International Conference on Learning Representations , URL https://openreview.net/forum?id=ByxBFsRqYm
2019
Later among the works it cites.
Selsam D, Lamm M, Bünz B, Liang P, de Moura L, Dill DL (2019) Learning a SAT solver from single-bit supervision. 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019 , URL https://openreview.net/forum?id=HJMC_iA5tm
2019
Later among the works it cites.
Tjeng V, Xiao KY, Tedrake R (2019) Evaluating robustness of neural networks with mixed integer programming. International Conference on Learning Representations , URL https://openreview.net/forum?id=HyGIdiRqtm
2019
Later among the works it cites.
Yang Y, Boland N, Savelsbergh M (2019) Multi-variable branching: A case study with 0-1 knapsack problems. Technical report, URL http://www.optimization-online.org/DB_HTML/2019/10/7431.html
2019
Later among the works it cites.
Addanki R, Nair V, Alizadeh M (2020) Neural large neighborhood search. Learning Meets Combinatorial Algorithms NeurIPS Workshop
2020
Closest in time.
Ding J, Zhang C, Shen L, Li S, Wang B, Xu Y, Song L (2020) Accelerating primal solution findings for mixed integer programs based on solution prediction. AAAI , URL https://www.aaai.org/Papers/AAAI/2020GB/AAAI-DingJ.6745.pdf
2020
Closest in time.
FICO Xpress (2020) FICO Xpress optimization suite. URL https://www.fico.com/en/products/fico-xpress-optimization
2020
Closest in time.
Gamrath G, Anderson D, Bestuzheva K, Chen WK, Eifler L, Gasse M, Gemander P, Gleixner A, Gottwald L, Halbig K, et al. (2020) The SCIP optimization suite 7.0
2020
Closest in time.
Gupta P, Gasse M, Khalil E, Mudigonda P, Lodi A, Bengio Y (2020) Hybrid models for learning to branch. Advances in neural information processing systems 33
2020
Closest in time.
Gurobi Optimization L (2020) Gurobi optimizer reference manual. URL http://www.gurobi.com
2020
Closest in time.
Tang Y, Agrawal S, Faenza Y (2020) Reinforcement learning for integer programming: Learning to cut. III HD, Singh A, eds., Proceedings of the 37th International Conference on Machine Learning , volume 119 of Proceedings of Machine Learning Research , 9367–9376 (Virtual: PMLR), URL http://proceedings.mlr.press/v119/tang20a.html
2020
Closest in time.
Xavier AS, Qiu F, Ahmed S (2020) Learning to solve large-scale security-constrained unit commitment problems. INFORMS Journal on Computing
2020
Closest in time.
Yang Y, Boland N, Dilkina B, Savelsbergh M (2020) Learning generalized strong branching for set covering, set packing, and 0-1 knapsack problems. Technical report, URL http://www.optimization-online.org/DB_HTML/2020/02/7626.html
2020
Closest in time.