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Pré-Publication, Document De Travail Année : 2016

COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting

Résumé

COCO is a platform for Comparing Continuous Optimizers in a black-box setting. It aims at automatizing the tedious and repetitive task of benchmarking numerical optimization algorithms to the greatest possible extent. We present the rationals behind the development of the platform as a general proposition for a guideline towards better benchmarking. We detail underlying fundamental concepts of COCO such as its definition of a problem, the idea of instances, the relevance of target values, and runtime as central performance measure. Finally, we give a quick overview of the basic code structure and the available test suites.
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Dates et versions

hal-01294124 , version 1 (27-03-2016)
hal-01294124 , version 2 (23-05-2016)
hal-01294124 , version 3 (28-07-2016)
hal-01294124 , version 4 (26-08-2020)

Identifiants

Citer

Nikolaus Hansen, Anne Auger, Olaf Mersmann, Tea Tusar, Dimo Brockhoff. COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting. 2016. ⟨hal-01294124v1⟩
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