460 citations · 783 across the 6 of their papers we have counts for
8 papers
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…