skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: A hybrid differential evolution/Levenberg-Marquardt method for solving inverse transport problems

Conference ·
OSTI ID:1024348

Recently, the Differential Evolution (DE) optimization method was applied to solve inverse transport problems in finite cylindrical geometries and was shown to be far superior to the Levenberg-Marquardt optimization method at finding a global optimum for problems with several unknowns. However, while extremely adept at finding a global optimum solution, the DE method often requires a large number (hundreds or thousands) of transport calculations, making it much slower than the Levenberg-Marquardt method. In this paper, a hybridization of the Differential Evolution and Levenberg-Marquardt approaches is presented. This hybrid method takes advantage of the robust search capability of the Differential Evolution method and the speed of the Levenberg-Marquardt technique.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC52-06NA25396
OSTI ID:
1024348
Report Number(s):
LA-UR-10-00032; LA-UR-10-32; TRN: US1104720
Resource Relation:
Conference: American Nuclear Society Annual Meeting ; June 13, 2010 ; San Diego, CA
Country of Publication:
United States
Language:
English

Similar Records

Application of the Differential Evolution Method to Solving Inverse Transport Problems
Journal Article · Sat Jan 01 00:00:00 EST 2011 · Nuclear Science and Engineering · OSTI ID:1024348

USING THE LEVENBERG-MARQUARDT METHOD FOR SOLUTIONS OF INVERSE TRANSPORT PROBLEMS IN ONE- AND TWO-DIMENSIONAL GEOMETRIES
Journal Article · Sat Jan 01 00:00:00 EST 2011 · Nuclear Technology · OSTI ID:1024348

Solving Inverse Transport Problems with Neutron Multiplication Measurements and Improved Differential Evolution
Journal Article · Sat Jul 01 00:00:00 EDT 2017 · Transactions of the American Nuclear Society · OSTI ID:1024348