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Title:Solving Nonlinear Constrained Optimization Problems Through Constraint Partitioning
Author(s):Chen, Yixin
Doctoral Committee Chair(s):Wah, Benjamin W.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Artificial Intelligence
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.
Issue Date:2005
Type:Text
Language:English
Description:167 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.
URI:http://hdl.handle.net/2142/81677
Other Identifier(s):(MiAaPQ)AAI3198943
Date Available in IDEALS:2015-09-25
Date Deposited:2005


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