余弦自适应混沌被囊体种群优化算法

doi:10.3778/j.issn.1002-8331.2108-0237

摘要/Abstract

摘要： 针对被囊体种群优化算法存在易陷入局部最优、收敛速度慢等缺点，提出一种余弦自适应混沌被囊体种群优化算法。在模拟被囊体喷射推进行为中，引入余弦自适应曲线计算搜索个体间的社会作用力，从而改进算法易出现早熟的问题；并在搜索个体向最佳位置移动上增加了一种混沌行为，使其避免局部最优并拥有更快的收敛速度。采用多种标准测试函数进行测试，实验结果表明，提出的新的被囊群优化算法在保留原有算法优点的基础上具有更好的收敛速度、精度和全局最优性。

关键词: 群智能优化, 被囊体优化算法, 混沌搜索, 自适应曲线, 混合算法

Abstract: Aiming at the shortcoming of tunicate swarm algorithm, such as easy to fall into local optimum and slow convergence speed, a chaotic tunicate swarm algorithm based on cosine adaptive is proposed in this paper. In the simulation of the capsule jet propulsion behavior, the cosine adaptive curve is introduced to calculate the social forces between individuals, so that the improved algorithm is prone to prematurity. In addition, a chaotic behavior is added when the search individual moves to the optimal position, which makes the search individual avoid local optimum and has faster convergence speed. Finally, a variety of standard test functions are used to test, and the experimental results show that the new encapsulated swarm optimization algorithm proposed in this paper has better convergence speed, precision and global optimality while retaining the advantages of the original algorithm.

Key words: swarm intelligent algorithm, tunicate swarm algorithm, chaos search, adaptive curve, hybrid algorithm

李湘喆, 顾磊, 马丽, 王梦杰. 余弦自适应混沌被囊体种群优化算法[J]. 计算机工程与应用, 2023, 59(2): 65-75.

LI Xiangzhe, GU Lei, MA Li, WANG Mengjie. Chaotic Tunicate Swarm Algorithm Based on Cosine Adaptive[J]. Computer Engineering and Applications, 2023, 59(2): 65-75.

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