Continuous and discrete optimization techniques for some problems in industrial engineering and materials design

This work comprises several projects that involve optimization of physical systems. By a physical system we understand an object or a process that is governed by physical, mechanical, chemical, biological, etc., laws. Such objects and the related optim...

Full description

Bibliographic Details
Main Author: Morenko, Yana
Other Authors: Krokhmal, Pavlo
Format: Others
Language:English
Published: University of Iowa 2015
Subjects:
Online Access:https://ir.uiowa.edu/etd/1991
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6328&context=etd
id ndltd-uiowa.edu-oai-ir.uiowa.edu-etd-6328
record_format oai_dc
spelling ndltd-uiowa.edu-oai-ir.uiowa.edu-etd-63282019-10-13T04:56:06Z Continuous and discrete optimization techniques for some problems in industrial engineering and materials design Morenko, Yana This work comprises several projects that involve optimization of physical systems. By a physical system we understand an object or a process that is governed by physical, mechanical, chemical, biological, etc., laws. Such objects and the related optimization problems are relatively rarely considered in operations research literature, where the traditional subjects of optimization methods are represented by schedules, assignments and allocations, sequences, and queues. The corresponding operations research and management sciences models result in optimization problems of relatively simple structure (for example, linear or quadratic optimization models), but whose difficulty comes from very large number (from hundreds to millions) of optimization variables and constraints. In contrast, in many optimization problems that arise in mechanical engineering, chemical engineering, biomedical engineering, the number of variables or constraints in relatively small (typically, in the range of dozens), but the objective function and constraints have very complex, nonlinear and nonconvex analytical form. In many problems, the analytical expressions for objective function and constraints may not be available, or are obtained as solutions of governing equations (e.g., PDE-onstrained optimization problems), or as results of external simulation runs (black-box optimization). In this dissertation we consider problems of classification of biomedical data, construction of optimal bounds on elastic tensor of composite materials, multiobjective (multi-property) optimization via connection to stochastic orderings, and black-box combinatorial optimization of crystal structures of organic molecules. 2015-12-01T08:00:00Z dissertation application/pdf https://ir.uiowa.edu/etd/1991 https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6328&context=etd Copyright 2015 Yana Morenko Theses and Dissertations eng University of IowaKrokhmal, Pavlo Zhupanska, Olesya I. publicabstract Industrial Engineering
collection NDLTD
language English
format Others
sources NDLTD
topic publicabstract
Industrial Engineering
spellingShingle publicabstract
Industrial Engineering
Morenko, Yana
Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
description This work comprises several projects that involve optimization of physical systems. By a physical system we understand an object or a process that is governed by physical, mechanical, chemical, biological, etc., laws. Such objects and the related optimization problems are relatively rarely considered in operations research literature, where the traditional subjects of optimization methods are represented by schedules, assignments and allocations, sequences, and queues. The corresponding operations research and management sciences models result in optimization problems of relatively simple structure (for example, linear or quadratic optimization models), but whose difficulty comes from very large number (from hundreds to millions) of optimization variables and constraints. In contrast, in many optimization problems that arise in mechanical engineering, chemical engineering, biomedical engineering, the number of variables or constraints in relatively small (typically, in the range of dozens), but the objective function and constraints have very complex, nonlinear and nonconvex analytical form. In many problems, the analytical expressions for objective function and constraints may not be available, or are obtained as solutions of governing equations (e.g., PDE-onstrained optimization problems), or as results of external simulation runs (black-box optimization). In this dissertation we consider problems of classification of biomedical data, construction of optimal bounds on elastic tensor of composite materials, multiobjective (multi-property) optimization via connection to stochastic orderings, and black-box combinatorial optimization of crystal structures of organic molecules.
author2 Krokhmal, Pavlo
author_facet Krokhmal, Pavlo
Morenko, Yana
author Morenko, Yana
author_sort Morenko, Yana
title Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
title_short Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
title_full Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
title_fullStr Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
title_full_unstemmed Continuous and discrete optimization techniques for some problems in industrial engineering and materials design
title_sort continuous and discrete optimization techniques for some problems in industrial engineering and materials design
publisher University of Iowa
publishDate 2015
url https://ir.uiowa.edu/etd/1991
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6328&context=etd
work_keys_str_mv AT morenkoyana continuousanddiscreteoptimizationtechniquesforsomeproblemsinindustrialengineeringandmaterialsdesign
_version_ 1719265278434476032