(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems
(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems
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(1 1)-CMA-ES 具有离散和混合整数问题的裕度
DOI：
10.1145/3583131.3590516
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Shinichi Shirakawa
中科院分区：
文献类型：
--
作者：
Yohei Watanabe;Kento Uchida;Ryoki Hamano;Shota Saito;Masahiro Nomura;Shinichi Shirakawa
协方差矩阵自适应进化策略（CMA-ES）是一种有效的连续黑箱优化方法。CMA-ES具有许多有吸引力的功能，包括不变性和良好的默认超参数设置。此外，已经提出了几个组件，专门的CMA-ES，如噪声处理和约束处理。为了在混合整数优化问题中利用这些优点，提出了带裕度的CMA-ES算法。带裕度的CMA-ES通过裕度修正来防止离散变量的早熟收敛，该修正通过修正分布参数来保留离散变量变化的生成概率。边缘校正已经应用于（μ/μw，Λ）-CMA-ES，而本文将边缘校正引入到（1+1）-CMA-ES中，这是CMA-ES的一个精英版本。（1+1）-CMA-ES通常对单峰函数有利，并且计算成本较低。为了解决混合整数优化的性能恶化，我们使用离散化的精英解决方案作为采样分布的平均值，并修改边缘校正不移动精英解决方案。在混合整数、整数和二进制域上使用基准函数进行的数值模拟表明，（1+1）-CMA-ES在特定搜索域上的性能优于带余量的CMA-ES，并且优于或可与几种专门的方法相媲美。
The covariance matrix adaptation evolution strategy (CMA-ES) is an efficient continuous black-box optimization method. The CMA-ES possesses many attractive features, including invariance properties and a well-tuned default hyperparameter setting. Moreover, several components to specialize the CMA-ES have been proposed, such as noise handling and constraint handling. To utilize these advantages in mixed-integer optimization problems, the CMA-ES with margin has been proposed. The CMA-ES with margin prevents the premature convergence of discrete variables by the margin correction, in which the distribution parameters are modified to leave the generation probability for changing the discrete variable. The margin correction has been applied to (μ/μw,Λ)-CMA-ES, while this paper introduces the margin correction into (1+1)-CMA-ES, an elitist version of CMA-ES. The (1+1)-CMA-ES is often advantageous for unimodal functions and can be computationally less expensive. To tackle the performance deterioration on mixed-integer optimization, we use the discretized elitist solution as the mean of the sampling distribution and modify the margin correction not to move the elitist solution. The numerical simulation using benchmark functions on mixed-integer, integer, and binary domains shows that (1+1)-CMA-ES with margin outperforms the CMA-ES with margin and is better than or comparable with several specialized methods to a particular search domain.
一种基于仿真的优化方法，用于分析急诊室网络中的救护车改道现象
DOI：
--
发表时间：
2021
期刊：
arXiv.org
影响因子：
--
作者：
Christian Piermarini;M. Roma
通讯作者：
M. Roma
影响因子：
4.6
作者：
Zhang, Yichi;Apley, Daniel W.;Chen, Wei
通讯作者：
Chen, Wei