全局优化和约束工程中的正弦余弦混合非线性大蔗鼠算法。

IF 3.9 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY
Jinzhong Zhang, Anqi Jin, Tan Zhang
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引用次数: 0

摘要

大蔗鼠算法(greater cane rat algorithm, GCRA)是一种受大蔗鼠识别和智能觅食行为启发的群体智能算法,该算法有利于大蔗鼠在雨季交配和在旱季不交配。但是,基本GCRA存在参数灵敏度高、解精度不够、计算量大、易出现局部最优和过拟合、动态适应性差、维数恶化严重等严重缺陷。提出了一种求解基准函数和约束工程设计的正弦余弦混合非线性大鼠算法(SCGCRA);目标是平衡勘探和开采,以确定全局最优的精确解决方案。SCGCRA利用正弦余弦算法的周期性振荡波动特性和非线性控制策略的动态调节和决策,提高搜索效率和灵活性,提高收敛速度和求解精度,增加种群多样性和质量,避免过早收敛和搜索停滞,弥补勘探与开发之间的不平衡,实现协同互补,降低灵敏度。实现反复膨胀和收缩。利用23个基准函数和6个实际工程设计验证了SCGCRA的可靠性和实用性。实验结果表明,SCGCRA具有较快的收敛速度、较高的求解精度、较强的稳定性和鲁棒性,具有一定的优越性和适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Nonlinear Greater Cane Rat Algorithm with Sine-Cosine Algorithm for Global Optimization and Constrained Engineering Applications.

The greater cane rat algorithm (GCRA) is a swarm intelligence algorithm inspired by the discerning and intelligent foraging behavior of the greater cane rats, which facilitates mating during the rainy season and non-mating during the dry season. However, the basic GCRA exhibits serious drawbacks of high parameter sensitivity, insufficient solution accuracy, high computational complexity, susceptibility to local optima and overfitting, poor dynamic adaptability, and a severe curse of dimensionality. In this paper, a hybrid nonlinear greater cane rat algorithm with sine-cosine algorithm named (SCGCRA) is proposed for resolving the benchmark functions and constrained engineering designs; the objective is to balance exploration and exploitation to identify the globally optimal precise solution. The SCGCRA utilizes the periodic oscillatory fluctuation characteristics of the sine-cosine algorithm and the dynamic regulation and decision-making of nonlinear control strategy to improve search efficiency and flexibility, enhance convergence speed and solution accuracy, increase population diversity and quality, avoid premature convergence and search stagnation, remedy the disequilibrium between exploration and exploitation, achieve synergistic complementarity and reduce sensitivity, and realize repeated expansion and contraction. Twenty-three benchmark functions and six real-world engineering designs are utilized to verify the reliability and practicality of the SCGCRA. The experimental results demonstrate that the SCGCRA exhibits certain superiority and adaptability in achieving a faster convergence speed, higher solution accuracy, and stronger stability and robustness.

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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
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