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基于非线性自适应比例因子的雪豹优化算法

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针对雪豹优化算法在求解复杂优化问题时，存在全局勘探能力不足、寻优精度低等问题，提出一种改进的雪豹优化算法。首先，基于分段Logistic混沌映射初始化从而提高初始种群多样性;其次，引入非线性比例因子用于平衡算法的全局勘探能力和局部开发能力;然后，提出了一种差分变异策略，在第一次种群更新位置后，使用5个随机个体提高全局搜索能力和算法收敛能力，在第二次种群更新位置后，使用3个随机个体保证在求解过程的中后期也具有一定的全局勘探能力，尽可能避免陷入局部最优。通过在IEEE CEC2022基准函数测试集上测试，并与其他算法进行比较，结果表明所提出的算法在种群质量、求解精度以及算法稳定性上均有较大提升。最后将所提出的算法应用于工程优化，计算结果进一步证实了算法的强优化能力。
Snow Leopard Optimization Algorithm for Nonlinear Adaptive Scaling Factor
An improved snow leopard optimization algorithm is proposed to solve complex optimization problems,such as insufficient global exploration ability and low optimization accuracy.Firstly,the initial population diversity is improved based on piecewise Logistic chaotic mapping initialization.Secondly,a nonlinear scaling factor is introduced to balance the global exploration ability and local devel-opment ability of the algorithm.Then,a differential variation strategy is proposed.After the first population update position,five random individuals are used to improve the global search ability and the convergence ability of the algorithm.After the second population update position,three random individuals are used to ensure the global exploration ability in the middle and late period of the solution process,so as to avoid falling into the local optimal as much as possible.The proposed algorithm is tested on IEEE CEC2022 benchmark function test set and compared with other algorithms.The results show that the proposed algorithm has great improvement in population quality,solving accuracy and algorithm stability.Finally,the proposed algorithm is applied to engineering optimization,and the calculation results further confirm its strong optimization ability.

snow leopard optimization algorithmchaotic mappingnonlinear adaptive scaling factordifferential evolution operatorconstraint optimization problems

崔铭悦、莫愿斌、王子豪、胡飓风

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广西民族大学人工智能学院,广西南宁 530006

广西混杂计算与集成电路设计分析重点实验室,广西南宁 530006

雪豹优化算法 混沌映射 非线性自适应比例因子 差分进化算子 约束优化问题

国家自然科学基金广西自然科学基金广西民族大学科研项目

21460082019GXNSFAA1850172021MDKJ004

2024

10.20165/j.cnki.ISSN1673-629X.2024.0032

计算机技术与发展
陕西省计算机学会

计算机技术与发展

CSTPCD
影响因子：0.621
ISSN：1673-629X
年,卷(期)：2024.34(4)
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