pith. sign in

arxiv: 1605.03560 · v1 · pith:DVK2KSPGnew · submitted 2016-05-11 · 💻 cs.NE

COCO: Performance Assessment

classification 💻 cs.NE
keywords assessmentperformancebenchmarkingcocotargetvaluesaggregationalgorithms
0
0 comments X
read the original 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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Better Understandings and Configurations in MaxSAT Local Search Solvers via Anytime Performance Analysis

    cs.AI 2024-03 unverdicted novelty 6.0

    ECDF-based anytime performance metrics improve both analysis of MaxSAT local search solver behavior and automatic hyperparameter configuration compared to final-fitness metrics.