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Personal profile

Education/Academic qualification

Chemical Engineering, PhD, Canegie Mellon University

… → 2002

Diplom-Mathematiker (Master’s degree equivalent in Mathematics), University of Cologne

… → 1997

Fingerprint Dive into the research topics where Andreas Waechter is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Nonlinear programming Engineering & Materials Science
Nonlinear Programming Mathematics
Nonlinear Optimization Mathematics
Line Search Mathematics
Global Convergence Mathematics
Mixed Integer Nonlinear Programming Mathematics
Sample Average Approximation Mathematics
Importance Sampling Mathematics

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Grants 2012 2022

Nonlinear programming
Constrained optimization
Importance sampling
Electric sparks
Complementarity Constraints
Convex Program
Quadratic Program
Mathematical Program with Complementarity Constraints

Research Output 2000 2019

3 Citations (Scopus)

A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization

Keskar, N. & Waechter, A., Jan 2 2019, In : Optimization Methods and Software. 34, 1, p. 150-171 22 p.

Research output: Contribution to journalArticle

Quasi-Newton Algorithm
Active Set
Nonsmooth Optimization
Constrained Optimization
Data storage equipment

Uniform convergence of sample average approximation with adaptive multiple importance sampling

Ben Feng, M., Maggiar, A., Staum, J. & Waechter, 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 proceedingConference contribution

Sample Average Approximation
Importance sampling
Importance Sampling
Uniform convergence
Uniform Law of Large numbers
2 Citations (Scopus)

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., Jan 1 2018, In : SIAM Journal on Optimization. 28, 2, p. 1478-1507 30 p.

Research output: Contribution to journalArticle

Trust Region Algorithm
Importance sampling
Importance Sampling
4 Citations (Scopus)
Free radical polymerization
Monte Carlo methods
2 Citations (Scopus)

A sequential algorithm for solving nonlinear optimization problems with chance constraints

Curtis, F. E., Wächter, A. & Zavala, V. M., Jan 1 2018, In : SIAM Journal on Optimization. 28, 1, p. 930-958 29 p.

Research output: Contribution to journalArticle

Chance Constraints
Sequential Algorithm
Nonlinear Optimization
Nonlinear Problem
Optimization Problem