ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at experimentalist scientists and applicable to process and product optimizations in various fields, this package simplifies the optimization process, offering features such as benchmarking, noise addition/removal, multiobjective optimization, batch-mode operation, and comprehensive plotting features. The present publication focuses on ease of use by presenting an optimization of a chemical reaction to produce a specific color, such as leaf green.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-02-07
DOI
https://doi.org/10.1021/acs.jcim.4c02240
Citations
6
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
8.91
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article

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

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Journal of Chemical Information and Modeling
Time Series Analysis and Forecasting
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article

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

Rolf H. Taaning, Sigurd Carlsen, Søren Bertelsen, Aksel Obdrup, Michael Nielsen, Søren Furbo
article en
6 citations

Abstract

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at experimentalist scientists and applicable to process and product optimizations in various fields, this package simplifies the optimization process, offering features such as benchmarking, noise addition/removal, multiobjective optimization, batch-mode operation, and comprehensive plotting features. The present publication focuses on ease of use by presenting an optimization of a chemical reaction to produce a specific color, such as leaf green.

Journal of Chemical Information and ModelingVol. 65(4)
Novo Nordisk (Denmark) (DK), Danish Technological Institute (DK), Digital Science (United States) (US), Haldor Topsoe (Denmark) (DK)
Openalex Percentile: Top 2%
Time Series Analysis and Forecasting
8.91
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