Pattern search algorithms for mixed variable general constrained optimization problems

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dc.contributor.advisorDennis, John E., Jr.en_US
dc.contributor.advisorAudet, Charlesen_US
dc.creatorAbramson, Mark Aaronen_US
dc.date.accessioned2009-06-04T08:19:00Zen_US
dc.date.available2009-06-04T08:19:00Zen_US
dc.date.issued2003en_US
dc.description.abstractA new class of algorithms for solving nonlinearly constrained mixed variable optimization problems is presented. The Audet-Dennis Generalized Pattern Search (GPS) algorithm for bound constrained mixed variable optimization problems is extended to problems with general nonlinear constraints by incorporating a filter, in which new iterates are accepted whenever they decrease the incumbent objective function value or constraint violation function value. Additionally, the algorithm can exploit any available derivative information (or rough approximation thereof) to speed convergence without sacrificing the flexibility often employed by GPS methods to find better local optima. In generalizing existing GPS algorithms, the new theoretical convergence results presented here reduce seamlessly to existing results for more specific classes of problems. While no local continuity or smoothness assumptions are made, a hierarchy of theoretical convergence results is given, in which the assumptions dictate what can be proved about certain limit points of the algorithm. A new Matlab(c) software package was developed to implement these algorithms. Numerical results are provided for several nonlinear optimization problems from the CUTE test set, as well as a difficult nonlinearly constrained mixed variable optimization problem in the design of a load-bearing thermal insulation system used in cryogenic applications.en_US
dc.format.extent180 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS MATH.SCI. 2003 ABRAMSONen_US
dc.identifier.citationAbramson, Mark Aaron. "Pattern search algorithms for mixed variable general constrained optimization problems." (2003) Diss., Rice University. <a href="https://hdl.handle.net/1911/18502">https://hdl.handle.net/1911/18502</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/18502en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectMathematicsen_US
dc.subjectEngineeringen_US
dc.subjectMaterials scienceen_US
dc.subjectOperations researchen_US
dc.titlePattern search algorithms for mixed variable general constrained optimization problemsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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