Using a derivativefree optimization method for multiple solutions of inverse transport problems
Abstract
Identifying unknown components of an object that emits radiation is an important problem for national and global security. Radiation signatures measured from an object of interest can be used to infer object parameter values that are not known. This problem is called an inverse transport problem. An inverse transport problem may have multiple solutions and the most widely used approach for its solution is an iterative optimization method. This paper proposes a stochastic derivativefree global optimization algorithm to find multiple solutions of inverse transport problems. The algorithm is an extension of a multilevel single linkage (MLSL) method where a mesh adaptive direct search (MADS) algorithm is incorporated into the local phase. Furthermore, numerical test cases using uncollided fluxes of discrete gammaray lines are presented to show the performance of this new algorithm.
 Authors:

 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Publication Date:
 Research Org.:
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Sponsoring Org.:
 USDOE
 OSTI Identifier:
 1247138
 Report Number(s):
 LAUR1429126
Journal ID: ISSN 13894420; PII: 9306
 Grant/Contract Number:
 AC5206NA25396
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Optimization and Engineering
 Additional Journal Information:
 Journal Volume: 17; Journal Issue: 1; Journal ID: ISSN 13894420
 Country of Publication:
 United States
 Language:
 English
 Subject:
 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; inverse transport problem; derivativefree optimization; stochastic global optimization; multilevel single linkage; mesh adaptive direct search
Citation Formats
Armstrong, Jerawan C., and Favorite, Jeffrey A. Using a derivativefree optimization method for multiple solutions of inverse transport problems. United States: N. p., 2016.
Web. doi:10.1007/s110810159306x.
Armstrong, Jerawan C., & Favorite, Jeffrey A. Using a derivativefree optimization method for multiple solutions of inverse transport problems. United States. doi:10.1007/s110810159306x.
Armstrong, Jerawan C., and Favorite, Jeffrey A. Thu .
"Using a derivativefree optimization method for multiple solutions of inverse transport problems". United States. doi:10.1007/s110810159306x. https://www.osti.gov/servlets/purl/1247138.
@article{osti_1247138,
title = {Using a derivativefree optimization method for multiple solutions of inverse transport problems},
author = {Armstrong, Jerawan C. and Favorite, Jeffrey A.},
abstractNote = {Identifying unknown components of an object that emits radiation is an important problem for national and global security. Radiation signatures measured from an object of interest can be used to infer object parameter values that are not known. This problem is called an inverse transport problem. An inverse transport problem may have multiple solutions and the most widely used approach for its solution is an iterative optimization method. This paper proposes a stochastic derivativefree global optimization algorithm to find multiple solutions of inverse transport problems. The algorithm is an extension of a multilevel single linkage (MLSL) method where a mesh adaptive direct search (MADS) algorithm is incorporated into the local phase. Furthermore, numerical test cases using uncollided fluxes of discrete gammaray lines are presented to show the performance of this new algorithm.},
doi = {10.1007/s110810159306x},
journal = {Optimization and Engineering},
number = 1,
volume = 17,
place = {United States},
year = {2016},
month = {1}
}