优化算法测试函数综述及应用分析
Summary and Application Analysis of Optimization Algorithm Test Function
DOI: 10.12677/CSA.2021.1111267, PDF,  被引量    科研立项经费支持
作者: 石宏庆, 徐 榛：贵州省通信产业服务有限公司，贵州 贵阳；侯 庆：贵州省通信产业服务有限公司，贵州 贵阳;贵州大学计算机科学与技术学院，贵州 贵阳；李 坤：贵州大学计算机科学与技术学院，贵州 贵阳
关键词: 差分进化算法；优化算法测试函数；MATLAB；Differential Evolution Algorithm； Optimization Algorithm Test Function； MATLAB
摘要: 本文以优化算法测试函数为研究对象，以差分进化算法为研究实例，采用图形观察法、模型方法、实验研究法和文献研究法等研究方法，对常见的5种优化算法测试函数的数学原理、函数特征以及使用方法开展研究，包括Ackley函数、Griewank函数、Rastrigin函数、Schaffer函数和Sphere函数。通过学习优化算法测试函数原理和在MATLAB上对差分进化算法进行仿真实验设计，验证其在优化算法改进中的性能评估功能。实验结果表明，优化算法测试函数对算法改良的性能验证具有重要的研究意义。
Abstract: With optimization algorithm test functions as the research object, and the differential evolution algorithm as the research example, this paper adopts Graphical Observation Method, Model Method, Experimental Research Method and Literature Research Method, etc. in order to test the mathematical principles, function characteristics and usage methods of 5 common optimization algorithms, namely Ackley Function, Griewank Function, Rastrigin Function, Schaffer Function and Sphere Function. Through learning the principles of the optimization algorithm test functions and the simulation experiment designing of the differential evolution algorithm based on MATLAB, the performance verification function in the improvement of the optimization algorithms is verified. The experimental results show that the optimization algorithm test functions have important research significance for the performance verification of the algorithm improvement.
文章引用：石宏庆, 侯庆, 徐榛, 李坤. 优化算法测试函数综述及应用分析[J]. 计算机科学与应用, 2021, 11(11): 2633-2645. https://doi.org/10.12677/CSA.2021.1111267

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