Open Collections

Zhongda, Huang

University of British Columbia

A derivative-free optimization (DFO) method is an optimization method that does not make use of derivative information in order to find the optimal solution. It is advantageous for solving real-world problems in which the only information available about the objective function is the output for a specific input. In this thesis, we develop the framework for a DFO method, referred to as the DQL method. It is designed to be a versatile hybrid method capable of performing direct search, quadratic-model search, and line search all in the same method. We develop a series of different direct search, quadratic-model search, and line search strategies within this framework. The benchmark results indicate that each of these strategies has distinct advantages in different scenarios and that there is no clear winner. We develop the Smart DQL method by allowing the method to determine the optimal search strategies in various circumstances. The Smart DQL method is applied to the problem of solid tank design for 3D radiation dosimetry. We show that, given the same evaluation budget, the Smart DQL method produces a higher-quality solution than the Grid Search method that was originally employed by the UBCO 3D Radiation Dosimetry Research Group.

Text

2022-07-15

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/82155

Mathematics

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/