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ORCIDAndreas Wächter
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2020 – today
- 2024
[j34]Edoardo Vecchi
, Juraj Kardos, Malik Lechekhab, Andreas Wächter, Illia Horenko, Olaf Schenk:
Structure-exploiting interior-point solver for high-dimensional entropy-sparsified regression learning. J. Comput. Sci. 76: 102208 (2024)- [j33]Xinyi Luo, Andreas Wächter:
A Quadratically Convergent Sequential Programming Method for Second-Order Cone Programs Capable of Warm Starts. SIAM J. Optim. 34(3): 2943-2972 (2024) - 2023
- [j32]Ignacio Aravena, Daniel K. Molzahn, Shixuan Zhang, Cosmin G. Petra, Frank E. Curtis, Shenyinying Tu, Andreas Wächter, Ermin Wei, Elizabeth Wong, Amin Gholami, Kaizhao Sun, Xu Andy Sun, Stephen T. Elbert, Jesse Holzer, Arun Veeramany:
Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition. Oper. Res. 71(6): 1997-2014 (2023) - [j31]Frank E. Curtis, Daniel K. Molzahn, Shenyinying Tu, Andreas Wächter, Ermin Wei, Elizabeth Wong:
A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF. Oper. Res. 71(6): 2031-2044 (2023) - [j30]Harun Avci, Barry L. Nelson, Eunhye Song, Andreas Wächter:
Using Cache or Credit for Parallel Ranking and Selection. ACM Trans. Model. Comput. Simul. 33(4): 12:1-12:28 (2023) - 2022
- [c7]Mark Semelhago, Barry L. Nelson, Eunhye Song, Andreas Wächter:
Object-Oriented Implementation and Parallelization of the Rapid Gaussian Markov Improvement Algorithm. WSC 2022: 3158-3169 - [i3]Juan Ospina, David M. Fobes, Russell Bent, Andreas Wächter:
Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations with PowerModelsITD.jl. CoRR abs/2210.16378 (2022) - 2021
- [j29]Mark Semelhago, Barry L. Nelson, Eunhye Song, Andreas Wächter:
Rapid Discrete Optimization via Simulation with Gaussian Markov Random Fields. INFORMS J. Comput. 33(3): 915-930 (2021) - [c6]Deborah Walz, Andreas Wächter, Stefan Tomov, Konrad Heimbach, Matthias Weigold:
Energieeffizientes Kaltstartverhalten spanender Werkzeugmaschinen. GI-Jahrestagung 2021: 1193-1199 - 2020
- [j28]Francisco Jara-Moroni, John E. Mitchell, Jong-Shi Pang, Andreas Wächter:
An enhanced logical benders approach for linear programs with complementarity constraints. J. Glob. Optim. 77(4): 687-714 (2020) - [j27]Alejandra Peña-Ordieres, James R. Luedtke, Andreas Wächter:
Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation. SIAM J. Optim. 30(3): 2221-2250 (2020) - [i2]Shenyinying Tu, Andreas Wächter, Ermin Wei:
A Two-Stage Decomposition Approach for AC Optimal Power Flow. CoRR abs/2002.08003 (2020)
2010 – 2019
- 2019
- [j26]Nitish Shirish Keskar, Andreas Wächter:
A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization. Optim. Methods Softw. 34(1): 150-171 (2019) - 2018
- [j25]Hanyu Gao, Andreas Wächter, Ivan A. Konstantinov, Steven G. Arturo, Linda J. Broadbelt:
Application and comparison of derivative-free optimization algorithms to control and optimize free radical polymerization simulated using the kinetic Monte Carlo method. Comput. Chem. Eng. 108: 268-275 (2018) - [j24]Francisco Jara-Moroni, Jong-Shi Pang, Andreas Wächter:
A study of the difference-of-convex approach for solving linear programs with complementarity constraints. Math. Program. 169(1): 221-254 (2018) - [j23]Frank E. Curtis, Andreas Wächter, Victor M. Zavala:
A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints. SIAM J. Optim. 28(1): 930-958 (2018) - [j22]Alvaro Maggiar, Andreas Wächter, Irina S. Dolinskaya, Jeremy Staum:
A Derivative-Free Trust-Region Algorithm for the Optimization of Functions Smoothed via Gaussian Convolution Using Adaptive Multiple Importance Sampling. SIAM J. Optim. 28(2): 1478-1507 (2018) - [c5]Mingbin Ben Feng, Alvaro Maggiar, Jeremy Staum, Andreas Wächter:
Uniform convergence of sample Average Approximation with adaptive Multiple Importance Sampling. WSC 2018: 1646-1657 - 2017
- [c4]Mark Semelhago, Barry L. Nelson, Andreas Wächter, Eunhye Song:
Computational methods for optimization via simulation using Gaussian Markov Random Fields. WSC 2017: 2080-2091 - 2016
- [j21]Dennis Janka, Christian Kirches, Sebastian Sager, Andreas Wächter:
An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix. Math. Program. Comput. 8(4): 435-459 (2016) - [j20]Nitish Shirish Keskar, Jorge Nocedal, Figen Öztoprak, Andreas Wächter:
A second-order method for convex l1-regularized optimization with active-set prediction. Optim. Methods Softw. 31(3): 605-621 (2016) - 2015
- [j19]Travis C. Johnson, Christian Kirches, Andreas Wächter:
An Active-Set Method for Quadratic Programming Based On Sequential Hot-Starts. SIAM J. Optim. 25(2): 967-994 (2015) - 2014
- [j18]Frank E. Curtis, Travis C. Johnson, Daniel P. Robinson, Andreas Wächter:
An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization. SIAM J. Optim. 24(3): 1041-1074 (2014) - 2013
- [j17]Pierre Bonami, Jon Lee, Sven Leyffer, Andreas Wächter:
On branching rules for convex mixed-integer nonlinear optimization. ACM J. Exp. Algorithmics 18 (2013) - 2012
- [j16]Frank E. Curtis, Johannes Huber, Olaf Schenk, Andreas Wächter:
A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations. Math. Program. 136(1): 209-227 (2012) - 2011
- [c3]Giacomo Nannicini, Pietro Belotti, Jon Lee, Jeff T. Linderoth, François Margot, Andreas Wächter:
A Probing Algorithm for MINLP with Failure Prediction by SVM. CPAIOR 2011: 154-169 - 2010
- [j15]Frank E. Curtis, Olaf Schenk, Andreas Wächter:
An Interior-Point Algorithm for Large-Scale Nonlinear Optimization with Inexact Step Computations. SIAM J. Sci. Comput. 32(6): 3447-3475 (2010)
2000 – 2009
- 2009
- [j14]Pietro Belotti, Jon Lee, Leo Liberti, François Margot, Andreas Wächter:
Branching and bounds tighteningtechniques for non-convex MINLP. Optim. Methods Softw. 24(4-5): 597-634 (2009) - [j13]Jorge Nocedal, Andreas Wächter, Richard A. Waltz:
Adaptive Barrier Update Strategies for Nonlinear Interior Methods. SIAM J. Optim. 19(4): 1674-1693 (2009) - [j12]Frank E. Curtis, Jorge Nocedal, Andreas Wächter:
A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. 20(3): 1224-1249 (2009) - [c2]Claudia D'Ambrosio, Jon Lee, Andreas Wächter:
A Global-Optimization Algorithm for Mixed-Integer Nonlinear Programs Having Separable Non-convexity. ESA 2009: 107-118 - [i1]Andreas Wächter:
Short Tutorial: Getting Started With Ipopt in 90 Minutes. Combinatorial Scientific Computing 2009 - 2008
- [j11]Pierre Bonami, Lorenz T. Biegler, Andrew R. Conn, Gérard Cornuéjols, Ignacio E. Grossmann, Carl D. Laird, Jon Lee, Andrea Lodi, François Margot, Nicolas W. Sawaya, Andreas Wächter:
An algorithmic framework for convex mixed integer nonlinear programs. Discret. Optim. 5(2): 186-204 (2008) - [j10]Olaf Schenk, Andreas Wächter, Martin Weiser:
Inertia-Revealing Preconditioning For Large-Scale Nonconvex Constrained Optimization. SIAM J. Sci. Comput. 31(2): 939-960 (2008) - 2007
- [j9]Olaf Schenk, Andreas Wächter, Michael Hagemann:
Matching-based preprocessing algorithms to the solution of saddle-point problems in large-scale nonconvex interior-point optimization. Comput. Optim. Appl. 36(2-3): 321-341 (2007) - 2006
- [j8]Andreas Wächter, Lorenz T. Biegler:
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Math. Program. 106(1): 25-57 (2006) - 2005
- [j7]Andreas Wächter, Chandramouli Visweswariah, Andrew R. Conn:
Large-scale nonlinear optimization in circuit tuning. Future Gener. Comput. Syst. 21(8): 1251-1262 (2005) - [j6]Andreas Wächter, Lorenz T. Biegler:
Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence. SIAM J. Optim. 16(1): 1-31 (2005) - [j5]Andreas Wächter, Lorenz T. Biegler:
Line Search Filter Methods for Nonlinear Programming: Local Convergence. SIAM J. Optim. 16(1): 32-48 (2005) - 2003
- [j4]Tobias Jockenhövel, Lorenz T. Biegler, Andreas Wächter:
Dynamic optimization of the Tennessee Eastman process using the OptControlCentre. Comput. Chem. Eng. 27(11): 1513-1531 (2003) - [j3]André L. Tits, Andreas Wächter, Sasan Bakhtiari, Thomas J. Urban, Craig T. Lawrence:
A Primal-Dual Interior-Point Method for Nonlinear Programming with Strong Global and Local Convergence Properties. SIAM J. Optim. 14(1): 173-199 (2003) - 2002
- [j2]Roger Fletcher, Nicholas I. M. Gould, Sven Leyffer, Philippe L. Toint, Andreas Wächter:
Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming. SIAM J. Optim. 13(3): 635-659 (2002) - 2000
- [j1]Andreas Wächter, Lorenz T. Biegler:
Failure of global convergence for a class of interior point methods for nonlinear programming. Math. Program. 88(3): 565-574 (2000) - [c1]R. A. Bartlett, Andreas Wächter, Lorenz T. Biegler:
Active set vs. interior point strategies for model predictive control. ACC 2000: 4229-4233
Coauthor Index
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