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
- 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