Solving Nonlinear Constrained Optimization Problems Through Constraint Partitioning
Chen, Yixin
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Permalink
https://hdl.handle.net/2142/81677
Description
Title
Solving Nonlinear Constrained Optimization Problems Through Constraint Partitioning
Author(s)
Chen, Yixin
Issue Date
2005
Doctoral Committee Chair(s)
Wah, Benjamin W.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Artificial Intelligence
Language
eng
Abstract
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.
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