Radioactive source search problem and optimisation model based on meta-heuristic algorithm

Simple item page
dc.contributor.authorZhang, Min
dc.contributor.authorLu, Xuewen
dc.contributor.authorHoffman, Ettiene
dc.contributor.authorKharabsheh, Radwan
dc.contributor.authorXiao, Qianghua
dc.date.accessioned2022-05-22T11:45:18Z
dc.date.available2022-05-22T11:45:18Z
dc.date.copyright© 2021
dc.date.issued2022
dc.descriptionThis article is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in Applied Mathematics and Nonlinear Sciences (2022), available online at: https://doi.org/10.2478/amns.2021.2.00159
dc.description.abstractIn the process of rational development and utilisation of nuclear energy, people often face nuclear accidents such as lost and stolen radioactive sources; so, the means of searching for these sources quickly in highly radioactive environments is an important security challenge. In the past, these jobs were limited to workers specialising in nuclear technology. They used gamma-ray detection equipment to search for radioactive sources, but the search efficiency was low. The main purpose of this article is to design a meta-heuristic algorithm based on imitating professional technicians to locate radioactive sources in a computer-aided manner. At the same time, due to the complexity that may characterise the actual search, the search strategy must be optimised. The article established an intelligent random search model with human thinking. Finally, it was proved based on the mathematical theory that the complexity of the model search algorithm is linear, and the simulation experiment results show that the optimisation algorithm has good efficiency and fault tolerance. © 2021 Min Zhang et al., published by Sciendo 2021.
dc.description.sponsorshipThe research is supported by the Hunan Natural Science Foundation Project (No. 2019JJ40260).
dc.identifier.citationZhang, M., Lu, X., Hoffman, E., Kharabsheh, R., & Xiao, Q. (2022). Radioactive source search problem and optimisation model based on meta-heuristic algorithm. Applied Mathematics and Nonlinear Sciences. https://doi.org/10.2478/amns.2021.2.00159
dc.identifier.issn24448656
dc.identifier.urihttps://doi.org/10.2478/amns.2021.2.00159
dc.identifier.urihttp://hdl.handle.net/20.500.12519/659
dc.language.isoen_US
dc.publisherSciendo
dc.relationAuthors Affiliations : Zhang, M., School of Math and Physics, University of South China, Hengyang, China, School of Mathematics, Physics and Energy Engineering, Hengyang, China; Lu, X., Department of Mathematics and Statistics, University of Calgar, Calgary, AB T2N 1N4, Canada; Hoffman, E., Canadian University Dubai, Dubai, United Arab Emirates; Kharabsheh, R., Business Administration Economics and Administrative Science, Applied Science University Bahrain, Al Hidd, Bahrain; Xiao, Q., School of Math and Physics, University of South China, Hengyang, China
dc.relation.ispartofseriesApplied Mathematics and Nonlinear Sciences; 24448656
dc.rightsThis work is licensed under the Creative Commons Attribution 4.0 International License.
dc.rights.holderCopyright : © 2021 Min Zhang et al., published by Sciendo 2021.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcomplexity
dc.subjectnuclear radioactive source
dc.subjectrandom search algorithm
dc.titleRadioactive source search problem and optimisation model based on meta-heuristic algorithm
dc.typeArticle
dspace.entity.type

Files

Collections

General Management