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Black-box Optimization Benchmarking (BBOB)

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The Black-box Optimization Benchmarking (BBOB) workshop series provides an easy-to-use toolchain for benchmarking black-box optimization algorithms for continuous and mixed-integer domains and a place to present, compare, and discuss the performance of numerical black-box optimization algorithms. The former is realized through the Comparing Continuous Optimizers platform (Coco).
Scientific Area:
Optimization
Language/Environments:
Python
Target Group:
Basic
Link:
https://numbbo.github.io/workshops/
Cite as:
Nikolaus Hansen, Anne Auger, Raymond Ros, Olaf Mersmann, Tea Tušar, and Dimo Brockhoff. “COCO: A platform for comparing continuous optimizers in a black-box setting.” Optimization Methods and Software (2020): 1-31
Author of the review:
Ivo Nowak
HAW Hamburg


Reviews

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Eligius Hendrix


Actually, many box constrained optimization benchmarks exist in literature. This is a recent one, but does not refer a lot to other existing benchmarks.
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