Abstract: In order to improve the global exploration and local development performance of the arithmetic optimization algorithm, an arithmetic optimization algorithm（IX-AOA） based on the non-linear aperture imaging mechanism and the optimal position-guided search strategy with fine-tuning function is proposed. The adaptive adjustment of the arithmetic acceleration optimizer factor is a vertical update strategy based on the exploration and development purpose of the balanced algorithm, adjusts the algorithm exploration and development time allocation through the hyperbolic nature, and then realizes the algorithm’s self-update mechanism to achieve the effect of balancing algorithm exploration and development. It uses sigmoid activation in the optimal individual, the weight coefficient of the function adjusts the reasonable control mechanism of the search and development of the offspring position to achieve the goal of enriching high-quality candidate solutions. It introduces the principle of nonlinear aperture imaging to improve the search mechanism to optimize the stagnation of optimization caused by the phenomenon of coverage between candidate solutions. Finally, 8 benchmark functions and some CEC2014 and Wilcoxon rank sum tests are used to verify the superiority of the algorithm function optimization.

Key words: arithmetic optimization algorithm, non linear control parameters, sigmoid function, small hole imaging learning, CEC2014

摘要： 为提高算术优化算法的全局勘探和局部开发性能，提出基于非线性小孔成像机理以及具有微调功能最优位置引导搜索策略的算术优化算法（IX-AOA），自适应调整算术加速优化器因子是基于平衡算法勘探与开发目的一种纵向更新策略，通过双曲线性质调整算法勘探与开发时间分配，进而实现算法的自我更新机制，达到平衡算法勘探与开发的效果。在最优个体使用基于sigmoid激活函数的权重系数调整子代位置的搜索与开发的合理受控机理，达到丰富优质候选解的目标；引入非线性小孔成像原理改善搜索机制以优化候选解之间覆盖现象导致的寻优停滞局面，最后通过8个基准函数和部分CEC2014以及Wilcoxon秩和检测验证算法函数寻优的优越性。

关键词: 算术优化算法, 非线性控制参数, sigmoid函数, 小孔成像学习, CEC2014