Advanced

Population-based metaheuristic optimization in neutron optics and shielding design

DiJulio, D. D. LU ; Björgvinsdóttir, H. LU ; Zendler, C. LU and Bentley, P. M. LU (2016) In Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 835. p.157-162
Abstract

Population-based metaheuristic algorithms are powerful tools in the design of neutron scattering instruments and the use of these types of algorithms for this purpose is becoming more and more commonplace. Today there exists a wide range of algorithms to choose from when designing an instrument and it is not always initially clear which may provide the best performance. Furthermore, due to the nature of these types of algorithms, the final solution found for a specific design scenario cannot always be guaranteed to be the global optimum. Therefore, to explore the potential benefits and differences between the varieties of these algorithms available, when applied to such design scenarios, we have carried out a detailed study of some... (More)

Population-based metaheuristic algorithms are powerful tools in the design of neutron scattering instruments and the use of these types of algorithms for this purpose is becoming more and more commonplace. Today there exists a wide range of algorithms to choose from when designing an instrument and it is not always initially clear which may provide the best performance. Furthermore, due to the nature of these types of algorithms, the final solution found for a specific design scenario cannot always be guaranteed to be the global optimum. Therefore, to explore the potential benefits and differences between the varieties of these algorithms available, when applied to such design scenarios, we have carried out a detailed study of some commonly used algorithms. For this purpose, we have developed a new general optimization software package which combines a number of common metaheuristic algorithms within a single user interface and is designed specifically with neutronic calculations in mind. The algorithms included in the software are implementations of Particle-Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and a Genetic Algorithm (GA). The software has been used to optimize the design of several problems in neutron optics and shielding, coupled with Monte-Carlo simulations, in order to evaluate the performance of the various algorithms. Generally, the performance of the algorithms depended on the specific scenarios, however it was found that DE provided the best average solutions in all scenarios investigated in this work.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Metaheuristic, Monte-Carlo, Neutron optics, Optimization, Shielding
in
Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
volume
835
pages
6 pages
publisher
Elsevier
external identifiers
  • scopus:84983551907
  • wos:000386057800017
ISSN
0168-9002
DOI
10.1016/j.nima.2016.08.035
language
English
LU publication?
yes
id
cacdc431-951d-4fcf-a4dc-9b12a5e9cc77
date added to LUP
2016-10-13 09:53:40
date last changed
2017-01-01 08:36:35
@article{cacdc431-951d-4fcf-a4dc-9b12a5e9cc77,
  abstract     = {<p>Population-based metaheuristic algorithms are powerful tools in the design of neutron scattering instruments and the use of these types of algorithms for this purpose is becoming more and more commonplace. Today there exists a wide range of algorithms to choose from when designing an instrument and it is not always initially clear which may provide the best performance. Furthermore, due to the nature of these types of algorithms, the final solution found for a specific design scenario cannot always be guaranteed to be the global optimum. Therefore, to explore the potential benefits and differences between the varieties of these algorithms available, when applied to such design scenarios, we have carried out a detailed study of some commonly used algorithms. For this purpose, we have developed a new general optimization software package which combines a number of common metaheuristic algorithms within a single user interface and is designed specifically with neutronic calculations in mind. The algorithms included in the software are implementations of Particle-Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and a Genetic Algorithm (GA). The software has been used to optimize the design of several problems in neutron optics and shielding, coupled with Monte-Carlo simulations, in order to evaluate the performance of the various algorithms. Generally, the performance of the algorithms depended on the specific scenarios, however it was found that DE provided the best average solutions in all scenarios investigated in this work.</p>},
  author       = {DiJulio, D. D. and Björgvinsdóttir, H. and Zendler, C. and Bentley, P. M.},
  issn         = {0168-9002},
  keyword      = {Metaheuristic,Monte-Carlo,Neutron optics,Optimization,Shielding},
  language     = {eng},
  month        = {11},
  pages        = {157--162},
  publisher    = {Elsevier},
  series       = {Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment},
  title        = {Population-based metaheuristic optimization in neutron optics and shielding design},
  url          = {http://dx.doi.org/10.1016/j.nima.2016.08.035},
  volume       = {835},
  year         = {2016},
}