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An adaptive dung beetle optimizer based on a resilient annealing mechanism and its application to numerical problems and optimi-zation of Reed–Muller logic circuits
Affiliation(s): 1Key Laboratory of Agricultural Big Data of Hebei Province, Hebei Agricultural University, Baoding 071001, China;
moreAffiliation(s): 1Key Laboratory of Agricultural Big Data of Hebei Province, Hebei Agricultural University, Baoding 071001, China; 2School of Computer Science and Engineering, Beihang University, Beijing 100191, China; 3School of Electronic and Information Engineering, Beihang University, Beijing 100191, China;
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Lixin MIAO1, Zhenxue HE1, Xiaojun ZHAO1, Yijin WANG1, Xiaodan ZHANG1, Kui YU1,Limin XIAO2, Zhisheng HUO3. An adaptive dung beetle optimizer based on a resilient annealing mechanism and its application to numerical problems and optimi-zation of Reed–Muller logic circuits[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2400967
@article{title="An adaptive dung beetle optimizer based on a resilient annealing mechanism and its application to numerical problems and optimi-zation of Reed–Muller logic circuits", author="Lixin MIAO1, Zhenxue HE1, Xiaojun ZHAO1, Yijin WANG1, Xiaodan ZHANG1, Kui YU1,Limin XIAO2, Zhisheng HUO3", journal="Frontiers of Information Technology & Electronic Engineering", year="in press", publisher="Zhejiang University Press & Springer", doi="https://doi.org/10.1631/FITEE.2400967" }
%0 Journal Article %T An adaptive dung beetle optimizer based on a resilient annealing mechanism and its application to numerical problems and optimi-zation of Reed–Muller logic circuits %A Lixin MIAO1 %A Zhenxue HE1 %A Xiaojun ZHAO1 %A Yijin WANG1 %A Xiaodan ZHANG1 %A Kui YU1 %A Limin XIAO2 %A Zhisheng HUO3 %J Frontiers of Information Technology & Electronic Engineering %P %@ 2095-9184 %D in press %I Zhejiang University Press & Springer doi="https://doi.org/10.1631/FITEE.2400967"
TY - JOUR T1 - An adaptive dung beetle optimizer based on a resilient annealing mechanism and its application to numerical problems and optimi-zation of Reed–Muller logic circuits A1 - Lixin MIAO1 A1 - Zhenxue HE1 A1 - Xiaojun ZHAO1 A1 - Yijin WANG1 A1 - Xiaodan ZHANG1 A1 - Kui YU1 A1 - Limin XIAO2 A1 - Zhisheng HUO3 J0 - Frontiers of Information Technology & Electronic Engineering SP - EP - %@ 2095-9184 Y1 - in press PB - Zhejiang University Press & Springer ER - doi="https://doi.org/10.1631/FITEE.2400967"
Abstract: The dung beetle optimizer (DBO) is a metaheuristic algorithm with fast convergence and powerful search capabilities, which has shown excellent performance in solving various optimization problems. However, it suffers from the problems of easily falling into local optimal solutions and poor convergence accuracy when dealing with large-scale complex optimization problems. Therefore, we propose an adaptive dung beetle optimizer (ADBO) based on an elastic annealing mechanism to address these issues. First, the convergence factor is adjusted in a nonlinear decreasing manner to balance the requirements of global exploration and local exploitation to improve convergence speed and search quality; second, a greedy difference optimization strategy is intro-duced to increase population diversity, improve the global search capability, and avoid premature convergence; finally, the elastic annealing mechanism is used to perturb the randomly selected individuals, which helps the algorithm escape the local optimum to improve its solution quality and stability. Experimental results based on the CEC 2017 and CEC 2022 benchmark function sets and MCNC benchmark circuits verify the effectiveness, superiority, and universality of the ADBO.
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