一种引入过渡阶段和高斯变异的改进算术优化算法  

Improved Arithmetic Optimization Algorithm by Introducing Transition Stage and Gaussian Mutation

作　　者：张伟[1] 李世港 齐明楚 周徐虎 宋燕[1] ZHANG Wei;LI Shigang;QI Mingchu;ZHOU Xuhu;SONG Yan(Shanghai Key Laboratory of Modern Optical Systems,School of Optical-Electrical&Computer Engineering,University of Shanghai for Science&Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院、上海市现代光学系统重点实验室,上海200093

出　　处：《小型微型计算机系统》2024年第7期1568-1576,共9页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(62073223)资助;国家科学基金项目(11502145)资助;上海市自然科学基金项目(22ZR1443400)资助。

摘　　要：针对算术优化算法收敛精度低、易陷入局部最优等问题,提出了一种改进的过渡高斯算术优化算法,该算法将新的非线性过渡阶段与改进的高斯变异策略相结合.首先,为了更好地从勘探阶段的高离散度策略过渡到开发阶段的低离散度策略,提出过渡阶段策略,并通过比较三种曲线实验重构数学优化加速函数.其次,引入具有算术优化算法特性的高斯变异策略和边界函数策略,加强算法跳出局部区域的能力.最后,将改进后的算术优化算法与几种著名算法进行对比,并进行不同维度的可扩展性分析,验证了所提算法的有效性.此外,该算法在压力容器设计问题中进行了测试.实验结果表明,TGAOA具有优异的收敛精度、收敛速度和鲁棒性.Aiming at the problems of low convergence precision and easy to fall into local optimum in the arithmetic optimization algorithm,an improved transitional Gaussian arithmetic optimization algorithm is proposed,which combines the new nonlinear transition stage with the improved Gaussian mutation strategy.First of all,in order to better transition from the high-dispersion strategy in the exploration stage to the low-dispersion strategy in the exploitation stage,a transition stage strategy is proposed,and three kinds of curve experiments are compared for reconstructing the mathematical optimization acceleration function.Secondly,the Gaussian mutation strategy and boundary function strategy are introduced to strengthen the algorithm’s ability to jump out of the local area,which have the characteristics of arithmetic optimization algorithm.Finally,the improved arithmetic optimization algorithm is compared with several well-known algorithms,and the scalability analysis of different dimensions is carried out to verify the effectiveness of the proposed algorithm.In addition,the algorithm is tested in the pressure vessel design problem.The experimental results show that TGAOA has excellent convergence accuracy,convergence speed and robustness.

关 键 词：算术优化算法 过渡阶段 高斯分布 压力容器设计 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]