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

Zhang, Min
Lu, Xuewen
Hoffman, Ettiene
Kharabsheh, Radwan
Xiao, Qianghua
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In 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.
This 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:
complexity, nuclear radioactive source, random search algorithm
Zhang, 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.