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Andreas Waechter

  • 5926 Citations
20002020

Research output per year

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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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Grants

Collaborative Research: Adaptive Gaussian Markov Random Fields for Large-scale Discrete Optimization via Simulation

Nelson, B. L. & Waechter, A.

National Science Foundation

7/15/19 → 6/30/22

Project: Research project

    • Hybrid Interior-Point/Active-Set PSCOPF Algorithms Exploiting Power System Characteristics

    Waechter, A. & Wei, E.

    Lehigh University, Advanced Research Projects Agency - Energy

    12/13/18 → 6/11/20

    Project: Research project

    • Algorithms for Nonlinear Nonconvex Optimization under Uncertainty

    Waechter, A.

    National Science Foundation

    9/15/15 → 8/31/19

    Project: Research project

    • Collaborative Research: Binary Constrained Convex Quadratic Programs with Complementarity Constraints and Extensions

    Waechter, A.

    National Science Foundation

    8/15/13 → 7/31/17

    Project: Research project

    • Novel Algorithms for Nonlinear Optimization

    Waechter, A.

    National Science Foundation

    8/1/12 → 7/31/15

    Project: Research project

    Research Output

    An enhanced logical benders approach for linear programs with complementarity constraints

    Jara-Moroni, F., Mitchell, J. E., Pang, J. S. & Wächter, A., Jan 1 2020, (Accepted/In press) In : Journal of Global Optimization.

    Research output: Contribution to journal › Article

    • 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

    • 4 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

    • 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. & Staum, J. C., Jan 1 2018, In : SIAM Journal on Optimization. 28, 2, p. 1478-1507 30 p.

    Research output: Contribution to journal › Article

    • 2 Scopus citations

    Application and comparison of derivative-free optimization algorithms to control and optimize free radical polymerization simulated using the kinetic Monte Carlo method

    Gao, H., Waechter, A., Konstantinov, I. A., Arturo, S. G. & Broadbelt, L. J., Jan 4 2018, In : Computers and Chemical Engineering. 108, p. 268-275 8 p.

    Research output: Contribution to journal › Article

    • 5 Scopus citations