A novel multi-objective optimization method, imperialist competitive algorithm, for fuel loading pattern of nuclear reactors

Akbari, Reza; Abbasi, Meisam; Faghihi, F.; Mirvakili, Seyed Mohammad; Mokhtari, J.

doi:10.1016/j.pnucene.2018.06.016

Cited by 19 publications

(2 citation statements)

References 14 publications

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“…In the past decade, nuclear engineers have tried to solve and reduce the complexity of this problem using metaheuristic optimization algorithms. Akbari et al (2018) have used the imperialist competitive algorithm for fuel loading pattern of a VVER-1000. Ahmad (2018) implemented the swarm intelligence algorithm for a material test reactor and also Hou Fig.…”

Section: Introductionmentioning

confidence: 99%

Small modular reactor full scope core optimization using Cuckoo Optimization Algorithm

Akbari

Ochbelagh

Gharib

et al. 2020

Progress in Nuclear Energy

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Section: Introductionmentioning

confidence: 99%

Small modular reactor full scope core optimization using Cuckoo Optimization Algorithm

Akbari

Ochbelagh

Gharib

et al. 2020

Progress in Nuclear Energy

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“…[20] ICA is a metaheuristic based on social and political behavior [21]. At present, the algorithm has been successfully applied to power grid energy management [22], nuclear reactor fuel loading [23], parameter estimation [24], production scheduling [25][26][27][28][29], and so on. According to literature [30], ICA not only is an effective global optimization method, but also has a strong neighborhood search capability.…”

Section: Introductionmentioning

confidence: 99%

A Novel Imperialist Competitive Algorithm for Multithreshold Image Segmentation

Wang¹,

Guo-hua

Liu³

2019

Mathematical Problems in Engineering

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Multithreshold image segmentation plays a very important role in computer vision and pattern recognition. However, the computational complexity of multithreshold image segmentation increases exponentially with the increasing number of thresholds. Thus, in this paper, a novel imperialist competitive algorithm is proposed to solve the multithreshold image segmentation problem. Firstly, a new strategy of revolution and assimilation is adopted to improve the search efficiency of the algorithm. Secondly, imperialist self-learning and reserve country set are introduced to enhance the search of outstanding individuals in the population. Combining with the reserve country set, a novel imperialist competition strategy is proposed to remove the poorer individuals and improve the overall quality of the population. Finally, the sensitivity of the algorithm parameters is analyzed. Ten standard test pictures are selected to test. The experimental results show that the novel imperialist competitive algorithm has faster convergence speed, higher quality, and higher stability in solving multithreshold segmentation problems than methods from literature.

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Artificial Intelligence (AI) in the Nuclear Power Plants: Who Is Liable When AI Fails to Perform

Karim¹,

Muhammad‐Sukki²

2022

The Handbook of Energy Policy

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A novel multi-objective optimization method, imperialist competitive algorithm, for fuel loading pattern of nuclear reactors

Cited by 19 publications

References 14 publications

Small modular reactor full scope core optimization using Cuckoo Optimization Algorithm

Small modular reactor full scope core optimization using Cuckoo Optimization Algorithm

A Novel Imperialist Competitive Algorithm for Multithreshold Image Segmentation

Artificial Intelligence (AI) in the Nuclear Power Plants: Who Is Liable When AI Fails to Perform

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