Back to results

University of Illinois at Urbana-Champaign

Solving Nonlinear Constrained Optimization Problems Through Constraint Partitioning

Abstract

dc:description

Our partition-and-resolve approach has achieved substantial improvements over existing methods in AI planning and mathematical programming. We have applied our method to solve some large-scale AI planning problems, as well as some continuous and mixed-integer NLPs in standard benchmarks. We have solved some large-scale problems that were not solvable by other leading methods and have improved the solution duality on many problems.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, Yixin
Contributors dc:contributor
  • Wah, Benjamin W.

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI3198943
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/81677

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Chen, Yixin. Solving Nonlinear Constrained Optimization Problems Through Constraint Partitioning. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/81677