CEC2017 Benchmark: Optimal Values and Deviations for 50-Dimensional Functions
by Yang Cao·Updated 1mo ago
17.1 KB1files
Available on 1 platform
Sign in to view source links and access this dataset
Description
30 runs of 8 evolutionary algorithms (DE, SaDE, SHADE, ILSHADE, jSO, MPEDE, LSHADE, RL-DE) on 29 test functions across 50 dimensions. The dataset contains the average optimal values and standard deviations from these runs, compiled by Yang Cao and shared under a CC-BY-4.0 license.
Use Cases
Benchmarking algorithm performance based on average optimal values and standard deviations.
Comparing the stability of different evolutionary algorithms based on results from 30 runs.
Analyzing the difficulty of 50-dimensional CEC2017 test functions based on algorithm outcomes.
Strengths
Results from 30 independent runs provide statistical reliability.
Compares 8 distinct evolutionary algorithms on a standard benchmark suite of 29 functions.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
Provenance
Source
figshare
Collection Method
Numerical results from computational experiments.
Freshness
Last updated 2026-05-13 17:44:40; freshness should be verified.
Dataset is very small (17.1 KB), indicating limited scope.