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Population-based metaheuristic optimization in neutron optics and shielding design
European Spallat Source ERIC, POB 176, SE-22100 Lund, Sweden.;Lund Univ, Div Nucl Phys, SE-22100 Lund, Sweden..
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Materials Physics. European Spallat Source ERIC, POB 176, SE-22100 Lund, Sweden..
European Spallat Source ERIC, POB 176, SE-22100 Lund, Sweden..
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Materials Physics. European Spallat Source ERIC, POB 176, SE-22100 Lund, Sweden..
2016 (English)In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, ISSN 0168-9002, E-ISSN 1872-9576, Vol. 835, p. 157-162Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2016. Vol. 835, p. 157-162
Keywords [en]
Metaheuristic, Optimization, Neutron optics, Shielding, Monte-Carlo
National Category
Accelerator Physics and Instrumentation
Identifiers
URN: urn:nbn:se:uu:diva-308632DOI: 10.1016/j.nima.2016.08.035ISI: 000386057800017OAI: oai:DiVA.org:uu-308632DiVA, id: diva2:1050843
Available from: 2016-11-30 Created: 2016-11-29 Last updated: 2017-11-29Bibliographically approved

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Bentley, Phillip M.

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