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Georgia Institute of Technology

Convexification and Global Optimization of Problems Involving the Euclidean Norm

Abstract

dc:description.abstract

The field of deterministic global optimization has advanced significantly over the last several decades, enabled by the development of new algorithmic techniques and improved computer hardware, and is experiencing a surge of interest. However, global optimization methods for general nonlinear problems are less mature than those for other NP-hard classes of optimization problems, such as mixed-integer linear or quadratic optimization. In this thesis, we study a particularly challenging class of nonconvex optimization problems, characterized by the presence of the Euclidean norm. These problems arise naturally in the context of chemical and statistical physics, but also appear in applications including discrete geometry and operations research, and the question of certifying global optimality remains open even for small instances. We identify the simultaneous elimination of Euclidean and permutational symmetry groups, as well as the convexification of reverse convex sets defined by the Euclidean norm, as two key challenges for global optimization methods, and introduce a benchmark library of instances of this type. Furthermore, we advance the state of the art by developing symmetry elimination and convexification techniques in the context of two problems arising in chemistry and physics and one from location theory. Numerical experiments with the general-purpose global optimization solver BARON indicate that our algorithms accelerate the solution of these problems by up to two orders of magnitude.

Degree

thesis:*
Level thesis:degree_level
Doctoral
Department dc:contributor.department
Chemical and Biomolecular Engineering
Grantor dc:publisher
Georgia Institute of Technology
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kuznetsov, Anatoliy
Advisor dc:contributor.advisor
  • Sahinidis, Nikolaos
Committee members dc:contributor.committeemember
  • Scott, Joseph K.
  • Wilson, Corey J.
  • Boukouvala, Fani
  • Skolnick, Jeffrey

Subjects

dc:subject × 3

Rights

Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1853/78549
OAI identifier oai:identifier
oai:repository.gatech.edu:1853/78549

Chain of custody

source
Harvested from
Georgia Tech
Base URL
repository.gatech.edu/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Kuznetsov, Anatoliy. Convexification and Global Optimization of Problems Involving the Euclidean Norm. Doctoral thesis, Georgia Institute of Technology, 2024. https://hdl.handle.net/1853/78549