460 citations · 1k across the 14 of their papers we have counts for
14 papers
Speeding Up Mixed-Integer Programming Solvers with Sparse Learning for Branching
Selin Bayramoğlu, George L Nemhauser, Nikolaos V Sahinidis
Machine learning is increasingly used to improve decisions within branch-and-bound algorithms for mixed-integer programming. Many existing approaches rely on deep learning, which o…
Constructing Tight Quadratic Relaxations for Global Optimization: II. Underestimating Difference-of-Convex (D.C.) Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
Recent advances in the efficiency and robustness of algorithms solving convex quadratically constrained quadratic programming (QCQP) problems motivate developing techniques for cre…
Constructing Tight Quadratic Relaxations for Global Optimization: I. Outer-Approximating Twice-Differentiable Convex Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency a…
A reformulation-enumeration MINLP algorithm for gas network design
Yijiang Li, Santanu S. Dey, Nikolaos V. Sahinidis
Gas networks are used to transport natural gas, which is an important resource for both residential and industrial customers throughout the world. The gas network design problem is…
Transfer Learning in Information Criteria-based Feature Selection
Shaohan Chen, Nikolaos V. Sahinidis, Chuanhou Gao
This paper investigates the effectiveness of transfer learning based on Mallows' Cp. We propose a procedure that combines transfer learning with Mallows' Cp (TLCp) and prove that i…
SDP-quality bounds via convex quadratic relaxations for global optimization of mixed-integer quadratic programs
Carlos J. Nohra, Arvind U. Raghunathan, Nikolaos V. Sahinidis
We consider the global optimization of nonconvex mixed-integer quadratic programs with linear equality constraints. In particular, we present a new class of convex quadratic relaxa…
A Discussion on Practical Considerations with Sparse Regression Methodologies
Owais Sarwar, Benjamin Sauk, Nikolaos V. Sahinidis
Sparse linear regression is a vast field and there are many different algorithms available to build models. Two new papers published in Statistical Science study the comparative pe…
Spectral relaxations and branching strategies for global optimization of mixed-integer quadratic programs
Carlos J. Nohra, Arvind U. Raghunathan, Nikolaos V. Sahinidis
We consider the global optimization of nonconvex quadratic programs and mixed-integer quadratic programs. We present a family of convex quadratic relaxations which are derived by c…
OR-Gym: A Reinforcement Learning Library for Operations Research Problems
Christian D. Hubbs, Hector D. Perez, Owais Sarwar +3
Reinforcement learning (RL) has been widely applied to game-playing and surpassed the best human-level performance in many domains, yet there are few use-cases in industrial or com…
Domain reduction techniques for global NLP and MINLP optimization
Yash Puranik, Nikolaos V. Sahinidis
Optimization solvers routinely utilize presolve techniques, including model simplification, reformulation and domain reduction techniques. Domain reduction techniques are especiall…
Simulation optimization: A review of algorithms and applications
Satyajith Amaran, Nikolaos V. Sahinidis, Bikram Sharda +1
Simulation Optimization (SO) refers to the optimization of an objective function subject to constraints, both of which can be evaluated through a stochastic simulation. To address…
The ALAMO approach to machine learning
Zachary T. Wilson, Nikolaos V. Sahinidis
ALAMO is a computational methodology for leaning algebraic functions from data. Given a data set, the approach begins by building a low-complexity, linear model composed of explici…
Optimization of circuitry arrangements for heat exchangers using derivative-free optimization
Nikolaos Ploskas, Christopher Laughman, Arvind U. Raghunathan +1
Optimization of the refrigerant circuitry can improve a heat exchanger's performance. Design engineers currently choose the refrigerant circuitry according to their experience and…
Computer-aided molecular design: An introduction and review of tools, applications, and solution techniques
Nick D. Austin, Nikolaos V. Sahinidis, Daniel W. Trahan
This article provides an introduction to and review of the field of computer-aided molecular design (CAMD). It is intended to be approachable for the absolute beginner as well as u…