ArticleScientific reports2022
The fusion-fission optimization (FuFiO) algorithm.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Energy efficient clustering protocol in wireless sensor networks using an adaptive hybrid optimization algorithm.Scientific reports · 2026Article
- Rank charged system search algorithm for optimization and operations research.Scientific reports · 2026Article
- A hybrid Prairie INFO fission naked algorithm with stagnation mechanism for the parametric estimation of solar photovoltaic systems.Scientific reports · 2025Article
- American zebra optimization algorithm for global optimization problems.Scientific reports · 2023Article
- An Improved Sparrow Search Algorithm and Its Application in HIFU Sound Field.Computational intelligence and neuroscience · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fusion-Fission Optimization (FuFiO) is proposed as a new metaheuristic algorithm that simulates the tendency of nuclei to increase their binding energy and achieve higher levels of stability. In this algorithm, nuclei are divided into two groups, namely stable and unstable. Each nucleus can interact with other nuclei using three different types of nuclear reactions, including fusion, fission, and β-decay. These reactions establish the stabilization process of unstable nuclei through which they gradually turn into stable nuclei. A set of 120 mathematical benchmark test functions are selected to evaluate the performance of the proposed algorithm. The results of the FuFiO algorithm and its related non-parametric statistical tests are compared with those of other metaheuristic algorithms to make a valid judgment. Furthermore, as some highly-complicated problems, the test functions of two recent Competitions on Evolutionary Computation, namely CEC-2017 and CEC-2019, are solved and analyzed. The obtained results show that the FuFiO algorithm is superior to the other metaheuristic algorithms in most of the examined cases.
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Registered trials
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