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Updated: May 29, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian
Søren Bertelsen1, Sigurd Carlsen2, Søren Furbo1
1Department of Automation and Process Optimisation, Digital Science and Innovation, Novo Nordisk A/S, 2760 Måløv, Denmark.
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.
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