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CEGO: C++11 Evolutionary Global Optimization

Published

Author(s)

Ian H. Bell

Abstract

Global optimization is an algorithmic need that is ubiquitous throughout the natural sciences, engineering, and other technical spheres. It is a non-trivial task, particularly when the function to be optimized has many local minima and the optimization algorithm may get trapped in the local minima of the function to be optimized. For that reason, many competing approaches have been proposed for the global optimization, especially nature-inspired global optimization approaches. The goal of the library proposed here is to develop a user-friendly framework in C++11 (with wrappers for Python) that can be used to successfully and efficiently carry out global optimization of challenging cost functions with a minimum of expertise required.
Citation
Journal of Open Source Software

Citation

Bell, I. (2019), CEGO: C++11 Evolutionary Global Optimization, Journal of Open Source Software, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926463 (Accessed May 17, 2024)

Issues

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Created April 23, 2019, Updated January 2, 2020