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引入人工偏好权重的混合型黑猩猩优化算法及应用

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为提高黑猩猩优化算法的收敛速度、求解精度和局部极值逃逸能力,提出一种引入人工偏好权重的混合型黑猩猩优化算法(HChOA)。首先,结合ChOA实际设计新的非线性收敛因子平衡算法全局和局部搜索能力;其次,在黑猩猩群体中引入"相异度"的概念和"趋异斥似"的人工偏好权重,以此优化黑猩猩位置更新公式,增强迭代末期种群多样性的同时加快算法收敛速度;最后,提出一种改进的算术优化算法(IAOA)并融入ChOA中,抽取部分黑猩猩个体执行IAOA优化策略,避免因领导者陷入局部最优而导致群体搜索停滞时出现早熟收敛现象。通过8个标准测试函数在多种维度下的数值对比实验以及1个工程设计问题的求解,综合分析验证了HChOA具有显著的优越性、稳定性和鲁棒性,且具备工程应用价值。
Hybrid chimp optimization algorithm with artificial preference weight and its application
A hybrid chimp optimization algorithm(HChOA)with artificial preference weight is proposed to improve the convergence speed,solution accuracy and local extreme escape ability of the chimp optimization algorithm.Firstly,combined with the actual situation of the ChOA,a new nonlinear convergence factor is designed for balancing global and local search capability.Secondly,the concept of"dissimilarity"and an artificial preference weight which can be described as"tendency difference and repulsion similarity"are introduced into the chimp population to optimize position update rule,enhance the population diversity at the end of iteration and accelerate the convergence speed of the algorithm.Finally,an improved arithmetic optimization algorithm(IAOA)and mixing into ChOA are proposed,we extract some chimp individuals to perform the IAOA optimization strategy to avoid group search stagnation and premature convergence caused by leader falling into local optimum.Through the numerical comparison experiments of 8 benchmark functions in various dimensions and the solution of one engineering design problem,the comprehensive analysis verifies that the HChOA has significant superiority,robusticity and the value of engineering application.

chimp optimization algorithmnonlinear convergence factorartificial preference weightarithmetic optimization algorithmengineering design optimizationdissimilarity

刘威、牛英杰、王东、刘光伟、马灵潇

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辽宁工程技术大学理学院,辽宁阜新 123000

辽宁工程技术大学智能工程与数学研究院,辽宁阜新 123000

辽宁工程技术大学矿业学院,辽宁阜新 123000

黑猩猩优化算法 非线性收敛因子 人工偏好权重 算术优化算法 工程设计优化 相异度

国家自然科学基金项目辽宁省教育厅项目辽宁工程技术大学学科创新团队项目辽宁工程技术大学学科创新团队项目

51974144LJKZ0340LNTU20TD-01LNTU20TD-07

2024

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子:1.227
ISSN:1001-0920
年,卷(期):2024.39(2)
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