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A mixed-integer convex (MI-convex) optimization problem is one that becomes convex when all integrality constraints are relaxed.
Algorithms and software for convex mixed integer nonlinear programs
P. Bonami, M. Kılınç, and J. Linderoth · 1926
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Perspective reformulation and applications
O. Günlük and J. Linderoth · 1926
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Subgradient based outer approximation for mixed integer second order cone programming
S. Drewes and S. Ulbrich · 1927
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An LP/NLP based branch and bound algorithm for convex MINLP optimization problems
I. Quesada and I. Grossmann · 1992
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Deterministic Methods for Mixed Integer Nonlinear Programming
S. Leyffer · 1993
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Csdp, ac library for semidefinite programming
B. Borchers · 1999
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Benchmarking optimization software with performance profiles
E. D. Dolan and J. J. Moré · 2002
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Second order cone programming relaxation of a positive semidefinite constraint
S. Kim, M. Kojima, and M. Yamashita · 2003
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Semidefinite programming relaxations for semialgebraic problems
P. A. Parrilo · 2003
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Convex Optimization
S. Boyd and L. Vandenberghe · 2004
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The COIN-OR Open Solver Interface: Technology overview
M. Saltzman, L. Ladáanyi, and T. Ralphs · 2004
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Disciplined convex programming
M. Grant, S. Boyd, and Y. Ye · 2006
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An algorithmic framework for convex mixed integer nonlinear programs
P. Bonami, L. T. Biegler, A. R. Conn, G. Cornuéjols, I. E. Grossmann, C. D. Laird, J. Lee, A. Lodi, F. Margot, N. Sawaya, and A. Wächter · 2008
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SCIP: Solving constraint integer programs
T. Achterberg · 2009
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Mixed-integer nonlinear optimization
P. Belotti, C. Kirches, S. Leyffer, J. Linderoth, J. Luedtke, and A. Mahajan · 2013
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ECOS: An SOCP solver for embedded systems
A. Domahidi, E. Chu, and S. Boyd · 2013
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Warmstarting the homogeneous and self-dual interior point method for linear and conic quadratic problems
A. Skajaa, E. D. Andersen, and Y. Ye · 2013
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Cvx: Matlab software for disciplined convex programming, version 2.1
M. Grant and S. Boyd · 2014
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Convex optimization in Julia
M. Udell, K. Mohan, D. Zeng, J. Hong, S. Diamond, and S. Boyd · 2014
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Lecture 4: The dual cone and dual problem
S. Zhang · 2014
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Extended formulations in mixed-integer convex programming
M. Lubin, E. Yamangil, R. Bent, and J. P. Vielma · 2016
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Modeling Cookbook revision 2.0.1
Mosek ApS · 2016
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Conic optimization via operator splitting and homogeneous self-dual embedding
B. O’Donoghue, E. Chu, N. Parikh, and S. Boyd · 2016
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Julia: A fresh approach to numerical computing
J. Bezanson, A. Edelman, S. Karpinski, and V. B. Shah · 2017
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JuMP: A modeling language for mathematical optimization
I. Dunning, J. Huchette, and M. Lubin · 2017
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A framework for solving mixed-integer semidefinite programs
T. Gally, M. E. Pfetsch, and S. Ulbrich · 2017
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A. A. Ahmadi and G. Hall · 2015
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Computing in operations research using Julia
M. Lubin and I. Dunning · 2015
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Solving conic optimization problems via self-dual embedding and facial reduction: a unified approach
F. Permenter, H. A. Friberg, and E. D. Andersen · 2015
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Algorithms for unsymmetric cone optimization and an implementation for problems with the exponential cone
S. A. Serrano · 2015
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CVXPY: A python-embedded modeling language for convex optimization
S. Diamond and S. Boyd · 2016
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CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization
H. A. Friberg · 2016
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Mixed-integer convex representability
M. Lubin, I. Zadik, and J. P. Vielma · 2017
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An adaptive, multivariate partitioning algorithm for global optimization of nonconvex programs
H. Nagarajan, M. Lu, S. Wang, R. Bent, and K. Sundar · 2017
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Extended formulations in mixed integer conic quadratic programming
J. P. Vielma, I. Dunning, J. Huchette, and M. Lubin · 2017
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Experiments with conflict analysis in mixed integer programming
J. Witzig, T. Berthold, and S. Heinz · 2017
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Juniper: An open-source nonlinear branch-and-bound solver in julia, 2018
O. Kröger, C. Coffrin, H. Hijazi, and H. Nagarajan · 2018
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Small and strong formulations for unions of convex sets from the cayley embedding
J. P. Vielma · 2018
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MINLPLIB2 library
S. Vigerske · 2018
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