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基于模型的全局优化方法综述

A Survey of Model-Based Methods for Global Optimization
课程网址: http://videolectures.net/bioma2016_bartz_beielstein_based_methods...  
主讲教师: Thomas Bartz-Beielstein
开课单位: TH Köln(应用科学大学)
开课时间: 2016-05-31
课程语种: 英语
中文简介:
本文描述了基于模型的全局优化方法。在引入全局优化框架后,给出了随机算法的建模方法。我们区分使用分布的模型和使用显式代理模型的模型。讨论了基于代理模型的优化的基本方面和最新进展。介绍了选择和评估代孕者的策略。文章最后描述了两种最先进的基于代理模型的算法的关键特征,即代理的进化学习(EvoLS)算法和序列参数优化(SPO)。 本讲座是一个项目的一部分,该项目根据第692286号拨款协议获得了欧盟地平线2020研究和创新计划的资助。
课程简介: This article describes model-based methods for global optimization. After introducing the global optimization framework, modeling approaches for stochastic algorithms are presented. We differentiate between models that use a distribution and models that use an explicit surrogate model. Fundamental aspects of and recent advances in surrogate-model based optimization are discussed. Strategies for selecting and evaluating surrogates are presented. The article concludes with a description of key features of two state-of-the-art surrogate model based algorithms, namely the evolvability learning of surrogates (EvoLS) algorithm and the sequential parameter optimization (SPO). This lecture is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 692286.
关 键 词: 全局优化; 建模方法; 随机算法
课程来源: 视频讲座网
数据采集: 2023-07-24:chenxin01
最后编审: 2023-07-24:chenxin01
阅读次数: 24