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http://dx.doi.org/10.1016/j.net.2021.05.018

Gamma ray interactions based optimization algorithm: Application in radioisotope identification  

Ghalehasadi, Aydin (Faculty of Physics, University of Tabriz)
Ashrafi, Saleh (Faculty of Physics, University of Tabriz)
Alizadeh, Davood (Faculty of Physics, University of Tabriz)
Meric, Niyazi (Institute of Nuclear Sciences, Ankara University)
Publication Information
Nuclear Engineering and Technology / v.53, no.11, 2021 , pp. 3772-3783 More about this Journal
Abstract
This work proposes a new efficient meta-heuristic optimization algorithm called Gamma Ray Interactions Based Optimization (GRIBO). The algorithm mimics different energy loss processes of a gamma-ray photon during its passage through a matter. The proposed novel algorithm has been applied to search for the global minima of 30 standard benchmark functions. The paper also considers solving real optimization problem in the field of nuclear engineering, radioisotope identification. The results are compared with those obtained by the Particle Swarm Optimization, Genetic Algorithm, Gravitational Search Algorithm and Grey Wolf Optimizer algorithms. The comparisons indicate that the GRIBO algorithm is able to provide very competitive results compared to other well-known meta-heuristics.
Keywords
Optimization; Meta-heuristic algorithms; Gamma ray interactions; GRIBO;
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