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A Comparative Assessment of Methodologies for Solving Problems of Nonlinear Optimization in the Business Sector

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abstract
Business professionals are seeking a solution to the problem of nonlinear optimization to maximize product value for the most respondents to a product survey. A comparative approach considers five methods of obtaining maximal solutions in minimal time. Simulated annealing and exhaustive enumeration seek to provide a family of solutions. Creating data warehouses using each of exhaustive enumeration, sampling with replacement, and sampling without replacement allows for more expedient analysis. Each method was assessed in terms of time requirements and quality of solution. Aside from exhaustive enumeration, the creation of a data warehouse that is a subset of all configurations via sampling without replacement provided near optimal families of solutions in minimal time.
subject
data sampling
data warehouse
parallel optimization
contributor
Freedman, Riana (author)
Santago II, Peter (committee chair)
Turkett, William H. (committee member)
Camm, Jeffrey D. (committee member)
date
2017-06-15T08:35:33Z (accessioned)
2019-06-14T08:30:13Z (available)
2017 (issued)
degree
Computer Science (discipline)
embargo
2019-06-14 (terms)
identifier
http://hdl.handle.net/10339/82169 (uri)
language
en (iso)
publisher
Wake Forest University
title
A Comparative Assessment of Methodologies for Solving Problems of Nonlinear Optimization in the Business Sector
type
Thesis

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