- Adolfo R. Escobedo and Erick Moreno-Centeno, "Roundoff-Error-Free Algorithms for Solving Linear Systems via Cholesky and LU Factorizations",
**INFORMS**Journal on Computing, 27 (2015), pp. 677-689. - Adolfo R. Escobedo and Erick Moreno-Centeno, "Roundoff-Error-Free Basis Updates of LU Factorizations for the Efficient Validation of Optimality Certificates",
**SIAM**Journal on Matrix Analysis and Applications, 38 (2017), pp. 829-853. - Adolfo R. Escobedo, Erick Moreno-Centeno, and Christopher Lourenco, "Solution of Dense Linear Systems via Roundoff-Error-Free Factorization Algorithms: Theoretical Connections and Computational Comparisons",
**ACM**Transactions on Mathematical Software, 44 (2018), pp. 1-24. - Christopher Lourenco, Adolfo R. Escobedo, Erick Moreno-Centeno, and Timothy Alden Davis, "Exact Solution of Sparse Linear Systems via Left-Looking Roundoff-Error-Free LU Factorization in Time Proportional to Arithmetic Work",
**SIAM**Journal on Matrix Analysis and Applications, 40 (2019), pp. 609-638.

The 2021 ICS Prize Committee members are:

- Ignacio Grossmann (CMU)
- Katya Scheinberg, Chair (Cornell)
- Suvrajeet Sen (USC)

2020 ICS Prize Winners

The 2020 INFORMS Computing Society prize is awarded to **Samuel Burer and Renato D. C. Monteiro** for their pioneering work on low-rank semidefinite programming, as detailed in the papers:

- A Nonlinear Programming Algorithm for Solving Semidefinite Programs via Low-Rank Factorization, Mathematical Programming Series B 95: 329–357, 2003.
- Local Minima and Convergence in Low-Rank Semidefinite Programming, Mathematical Programming Series A 103, 427–444, 2005.

The 2020 ICS Prize Committee members are:

- Suvrajeet Sen, Chair (USC)
- Necdet Serhat Aybat (PSU)
- Fatma Kilinc-Karzan (CMU)

The 2019 INFORMS Computing Society prize is awarded to **William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany L. Nicholson & John Siirola** for spearheading the creation and advancement of Pyomo, an open-source software package for modeling and solving mathematical programs in Python.

The 2019 ICS Prize Committee members are:

- Fatma Kilinc-Karzan (CMU)
- Thomas Sharkey (RPI)
- Douglas Shier, Chair (Clemson)

The 2018 INFORMS Computing Society prize is awarded to **James V. Burke**, **Frank E. Curtis**, **Adrian S. Lewis**, and **Michael L. Overton **for their pioneering work on gradient sampling methods for nonsmooth optimization, as detailed in the papers:

- "Approximating Subdifferentials by Random Sampling of Gradients.” Mathematics of Operations Research, 27:567-584, 2002.
- “A Sequential Quadratic Programming Algorithm for Nonconvex, Nonsmooth Constrained Optimization.” SIAM J. Optimization, 22(2):474-500, 2012.
- “A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization.” SIAM J. Optimization, 15(3):751-779, 2005.
- “A BFGS-SQP method for Nonsmooth, Nonconvex, Constrained Optimization and its Evaluation using Relative Minimization Profiles.” Optimization Methods and Software, 32(1):148-181, 2017.
- “Gradient Sampling Methods for Nonsmooth Optimization.” arXiv:1804.11003, 2018.

The 2018 ICS Prize Committee members are:

- Fatma Kilinc-Karzan (CMU)
- Andreas Waechter, Chair (Northwestern)
- Douglas Shier (Clemson)

The 2017 INFORMS Computing Society prize is awarded to **Shabbir Ahmed**, **George Nemhauser**, and **Juan Pablo Vielma **for their pioneering work on mixed integer linear programming formulations for piece-wise linear functions, as detailed in the papers:

- "Mixed-integer models for nonseparable piecewise linear optimization: unifying framework and extensions", Juan Pablo Vielma, Shabbir Ahmed and George Nemhauser, Operations Research, vol. 58, 303-315, 2010"
- "Modeling disjunctive constraints with a logarithmic number of binary variables and constraints", Juan Pablo Vielma and George Nemhauser, Mathematical Programming, vol. 128, 49-72, 2011.
- "Embedding Formulations and Complexity for Unions of Polyhedra", Juan Pablo Vielma, to appear in Management Science.

These papers develop advanced techniques to build mixed integer programming (MIP) formulations for disjunctive constraints with a special emphasis on piecewise linear (PWL) functions. The authors present comprehensive descriptions and comparisons of formulations for PWL functions and review in a unified manner the strength and quality measures of most known formulations. Before this body of work, the strongest-possible (ideal) formulations for PWL functions required many additional auxiliary variables. These papers introduce ideal formulations that are significantly smaller than previously known. In particular, the authors give an ideal formulation without continuous auxiliary variables whose size grows logarithmically with the size of the constraints. The final award-winning paper introduces a systematic geometric construction that generalizes the earlier work. In all cases, the authors give convincing evidence of the computational advantage given by the new formulations. The work has significant computational impact, especially in the area of non-convex optimization, where building piecewise linear approximations and relaxations of nonconvex functions is the state-of-the-art approach for solving this challenging class of problems.

2017 ICS Prize Selection Committee:

- Jon Lee (University of Michigan)
- Jeff Linderoth, Chair (University of Wisconsin-Madison)
- Jean-Paul Watson (Sandia National Laboratories)

2012-2016

2007-2011

2002-2006

Earlier