# COCO: Performance Assessment

Source: [COCO: Performance Assessment](<https://www.sota2.com/research/paper/68fa62811e209131ce9f9b37>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:31.814Z

Authors: Nikolaus Hansen, Anne Auger, Dimo Brockhoff, Dejan Tu\\v{s}ar, Tea Tu\\v{s}ar

Published: 2016-05-11T19:49:43.000Z

## Abstract

We present an any-time performance assessment for benchmarking numerical optimization algorithms in a black-box scenario, applied within the COCO benchmarking platform. The performance assessment is based on runtimes measured in number of objective function evaluations to reach one or several quality indicator target values. We argue that runtime is the only available measure with a generic, meaningful, and quantitative interpretation. We discuss the choice of the target values, runlength-based targets, and the aggregation of results by using simulated restarts, averages, and empirical distribution functions.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1605.03560>)

[PDF](<https://arxiv.org/pdf/1605.03560.pdf>)