11 citations · 17 across the 2 of their papers we have counts for
6 papers
Identifying Properties of Real-World Optimisation Problems through a Questionnaire
Koen van der Blom, Timo M. Deist, Vanessa Volz +5
Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match the properties of rea…
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems
Koen van der Blom, Timo M. Deist, Tea Tušar +5
Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate…
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite
Ouassim Elhara, Konstantinos Varelas, Duc Nguyen +4
The bbob-largescale test suite, containing 24 single-objective functions in continuous domain, extends the well-known single-objective noiseless bbob test suite, which has been use…
COCO: Performance Assessment
Nikolaus Hansen, Anne Auger, Dimo Brockhoff +2
We present an any-time performance assessment for benchmarking numerical optimization algorithms in a black-box scenario, applied within the COCO benchmarking platform. The perform…
Biobjective Performance Assessment with the COCO Platform
Dimo Brockhoff, Tea Tušar, Dejan Tušar +3
This document details the rationales behind assessing the performance of numerical black-box optimizers on multi-objective problems within the COCO platform and in particular on th…
COCO: The Experimental Procedure
Nikolaus Hansen, Tea Tusar, Olaf Mersmann +2
We present a budget-free experimental setup and procedure for benchmarking numericaloptimization algorithms in a black-box scenario. This procedure can be applied with the COCO ben…