Multi-objective optimization algorithm for expensive-to-evaluate function

版本 1.0.0.0 (896.5 KB) 作者: Artur Schweidtmann
Thompson sampling efficient multiobjective optimization (TSEMO) algorithm
5.0
(4)
1.9K 次下载
更新时间 2020/6/19
在 GitHub 上查看许可证

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO) algorithm [1].
The algorithm is designed for global multi-objective optimization of expensive-to-evaluate black-box functions. For example, the algorithm has been applied to the simultaneous optimization of the life-cycle assessment (LCA) and cost of a chemical process simulation [2]. However, the algorithm can be applied to other black-box function such as CFD simulations as well. It is based on the Bayesian optimization approach that builds Gaussian process surrogate models to accelerate optimization. Further, the algorithm can identify several promising points in each iteration (batch sequential mode). This allows to evaluate several simulations in parallel.
[1] Bradford, E., Schweidtmann, A.M. & Lapkin, A. J Glob Optim (2018). https://doi.org/10.1007/s10898-018-0609-2
[2] D. Helmdach, P. Yaseneva, P. K. Heer, A. M. Schweidtmann, A. A. Lapkin, ChemSusChem 2017, 10, 3632. https://doi.org/10.1002/cssc.201700927

引用格式

Artur Schweidtmann (2025). Multi-objective optimization algorithm for expensive-to-evaluate function (https://github.com/Eric-Bradford/TS-EMO), GitHub. 检索时间: .

MATLAB 版本兼容性
创建方式 R2018a
兼容任何版本
平台兼容性
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Direct

Mex_files/hypervolume

Mex_files/invchol

Mex_files/pareto front

NGPM_v1.4

Old_versions

Test_functions

无法下载基于 GitHub 默认分支的版本

版本 已发布 发行说明
1.0.0.0

added DOI of paper

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。