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Many-objective evolutionary algorithms based on reference-point-selection strategy for application in reactor radiation-shielding design

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Abstract

In recent years, the development of new types of nuclear reactors, such as transportable, marine, and space reactors, has presented new challenges for the optimization of reactor radiation-shielding design. Shielding structures typically need to be lightweight, miniaturized, and radiation-protected, which is a multi-parameter and multi-objective optimization problem. The conventional multi-objective (two or three objectives) optimization method for radiation-shielding design exhibits limitations for a number of optimization objectives and variable parameters, as well as a deficiency in achieving a global optimal solution, thereby failing to meet the requirements of shielding optimization for newly developed reactors. In this study, genetic and artificial bee-colony algorithms are combined with a reference-point-selection strategy and applied to the many-objective (having four or more objectives) optimal design of reactor radiation shielding. To validate the reliability of the methods, an optimization simulation is conducted on three-dimensional shielding structures and another complicated shielding-optimization problem. The numerical results demonstrate that the proposed algorithms outperform conventional shielding-design methods in terms of optimization performance, and they exhibit their reliability in practical engineering problems. The many-objective optimization algorithms developed in this study are proven to efficiently and consistently search for Pareto-front shielding schemes. Therefore, the algorithms proposed in this study offer novel insights into improving the shielding-design performance and shielding quality of new reactor types.

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Data availability

The data that support the findings of this study are openly available in Science Data Bank at https://cstr.cn/31253.11.sciencedb.j00186.00575 and https://doi.org/10.57760/sciencedb.j00186.00575.

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Authors and Affiliations

  1. School of Nuclear Science and Technology, University of South China, Hengyang, 421001, China

    Cheng-Wei Liu, Ai-Kou Sun, Ji-Chong Lei, Hong-Yu Qu, Chao Yang, Tao Yu & Zhen-Ping Chen

  2. Key Lab of Advanced Nuclear Energy Design and Safety, Ministry of Education, University of South China, Hengyang, 421000, China

    Cheng-Wei Liu, Ai-Kou Sun, Ji-Chong Lei, Hong-Yu Qu, Chao Yang, Tao Yu & Zhen-Ping Chen

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  1. Cheng-Wei Liu
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Cheng-Wei Liu, Ai-Kou Sun, Hong-Yu Qu, and Zhen-Ping Chen. The first draft of the manuscript was written by Cheng-Wei Liu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zhen-Ping Chen.

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The authors declare that they have no conflict of interest.

Additional information

This work was supported by the National Natural Science Foundation of China (Nos. 12475174 and 12175101) and YueLuShan Center Industrial Innovation (No. 2024YCII0108).

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Liu, CW., Sun, AK., Lei, JC. et al. Many-objective evolutionary algorithms based on reference-point-selection strategy for application in reactor radiation-shielding design. NUCL SCI TECH 36, 105 (2025). https://doi.org/10.1007/s41365-025-01683-7

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