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20172026
most citedSimulation optimization: A review of algorithms and applications

460 citations · 783 across the 7 of their papers we have counts for

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5 papers · 1 filter

math.OC2024

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…

math.OC2024

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…

math.OC2023

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…

math.OC2021

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…

math.OC2020

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…