Grants per year
Personal profile
Research Interests
Large-scale nonlinear continuous optimization; mixed-integer nonlinear optimization; open source software implementation; application of optimization algorithms to industrial and scientific problems.
Education/Academic qualification
Chemical Engineering, PhD, Carnegie Mellon University
… → 2002
Diplom-Mathematiker (Master’s degree equivalent in Mathematics), University of Cologne
… → 1997
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Network
Grants
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Collaborative Research: Adaptive Gaussian Markov Random Fields for Large-scale Discrete Optimization via Simulation
7/15/19 → 6/30/22
Project: Research project
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Hybrid Interior-Point/Active-Set PSCOPF Algorithms Exploiting Power System Characteristics
Lehigh University, Advanced Research Projects Agency - Energy
12/13/18 → 7/31/22
Project: Research project
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Algorithms for Nonlinear Nonconvex Optimization under Uncertainty
9/15/15 → 8/31/19
Project: Research project
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Collaborative Research: Binary Constrained Convex Quadratic Programs with Complementarity Constraints and Extensions
8/15/13 → 7/31/17
Project: Research project
Research Output
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An enhanced logical benders approach for linear programs with complementarity constraints
Jara-Moroni, F., Mitchell, J. E., Pang, J. S. & Wächter, A., Aug 1 2020, In: Journal of Global Optimization. 77, 4, p. 687-714 28 p.Research output: Contribution to journal › Article › peer-review
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Solving chance-constrained problems via a smooth sample-based nonlinear approximation
PENA-ORDIERES, ALEJANDRA., LUEDTKE, JAMES. R. & WACHTER, ANDREAS., 2020, In: SIAM Journal on Optimization. 30, 3, p. 2221-2250 30 p.Research output: Contribution to journal › Article › peer-review
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A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization
Keskar, N. & Wächter, A., Jan 2 2019, In: Optimization Methods and Software. 34, 1, p. 150-171 22 p.Research output: Contribution to journal › Article › peer-review
6 Scopus citations -
Uniform convergence of sample average approximation with adaptive multiple importance sampling
Ben Feng, M., Maggiar, A., Staum, J. C. & Wächter, A., Jan 31 2019, WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., p. 1646-1657 12 p. 8632370. (Proceedings - Winter Simulation Conference; vol. 2018-December).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
A derivative-free trust-region algorithm for the optimization of functions smoothed via Gaussian convolution using adaptive multiple importance sampling∗
Maggiar, A., Wächter, A., Dolinskaya, I. S. & Staum, J., 2018, In: SIAM Journal on Optimization. 28, 2, p. 1478-1507 30 p.Research output: Contribution to journal › Article › peer-review
2 Scopus citations