An Efficient Genetic Algorithm Based on Adaptive Boundary Constraint

doi:10.13209/j.0479-8023.2024.049

Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2024, Vol. 60 ›› Issue (4): 665-672.DOI: 10.13209/j.0479-8023.2024.049

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An Efficient Genetic Algorithm Based on Adaptive Boundary Constraint

HUANG Ming¹, WANG Longbo², XIAO Minghong¹, FU Yu¹, ZUO Zhengkang^3,†

1. Guangxi Zhuang Autonomous Region Institute of Geographical Information and Surveying, Liuzhou 545005 2. Department of Natural Resources, Guangxi Zhuang Autonomous Region, Nanning 530022 3. College of Mining Engineering Taiyuan University of Technology, Taiyuan 030024

Received:2023-07-25 Revised:2023-12-14 Online:2024-07-20 Published:2024-07-20
Contact: ZUO Zhengkang, E-mail: zuozhengkang(at)tyut.edu.cn

一种基于自适应边界约束的高效遗传算法

黄铭¹, 王龙波², 肖明虹¹, 傅毓¹, 左正康^3,†

1. 广西壮族自治区地理信息测绘院, 柳州 545005 2. 广西壮族自治区自然资源厅, 南宁 530022 3. 太原理工大学矿业工程学院, 太原 030024

通讯作者: 左正康, E-mail: zuozhengkang(at)tyut.edu.cn
基金资助:
太原理工大学引进人才科研启动经费(RY2400000591)资助

Abstract

Abstract:

According to the lack of method for highly efficiently spawning coefficients for multi-parent recombination in real-encoded genetic algorithm, an efficient genetic algorithm based on adaptive boundary constraint (ABC) is proposed. This method quickly generates coefficient vectors by adaptively scaling the boundary of the subsequent coefficient based on the value of the previous one, allowing for efficient reconstitution under any number of parent recombination scenarios. Experiment results on CEC2017 benchmarks demenstrate that proposed algorithm outperforms EDBF (empirical distribution based framework) a lot in 29 optimization problems.

Key words:

optimization theory, genetic algorithm, coefficient vector, convergence efficiency, empirical distribution based framework (EDBF), adaptive boundary constraint (ABC)

摘要：

针对遗传算法中用于多父体重组的系数向量缺乏高效生成方法的问题, 提出一种基于自适应边界约束(ABC)的高效遗传算法。该方法依据前一个系数的值, 自适应缩放后一个系数的边界, 可在任意多的父代重组情形下快速生成系数向量。在CEC2017标准数据集上的实验结果表明, 所提算法在29个复杂优化问题上的表现都优于经验概率分布(EDBF)算法。

关键词: 最优化理论, 遗传算法, 系数向量, 收敛效率, 经验概率分布(EDBF), 自适应边界约束(ABC)

HUANG Ming, WANG Longbo, XIAO Minghong, FU Yu, ZUO Zhengkang. An Efficient Genetic Algorithm Based on Adaptive Boundary Constraint[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2024, 60(4): 665-672.

黄铭, 王龙波, 肖明虹, 傅毓, 左正康. 一种基于自适应边界约束的高效遗传算法[J]. 北京大学学报自然科学版, 2024, 60(4): 665-672.

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URL: https://xbna.pku.edu.cn/EN/10.13209/j.0479-8023.2024.049

https://xbna.pku.edu.cn/EN/Y2024/V60/I4/665

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An Efficient Genetic Algorithm Based on Adaptive Boundary Constraint

一种基于自适应边界约束的高效遗传算法

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