Fixed Dimension Multimodal Benchmark Functions for Metaheuristic Testing

A set of benchmark functions used to evaluate the Felis Catus Optimization (FCO) metaheuristic algorithm. The dataset includes functions from the CEC 2005 and CEC 2017 benchmark suites. It was created by Mohammad Salehi and last updated on 2026-04-15.

Use Cases

• Benchmarking new optimization algorithms based on the CEC 2005 and CEC 2017 function suites.
• Testing algorithm performance on fixed-dimension multimodal problems as described in the study.
• Comparing convergence patterns and resilience against premature stagnation across different optimizers.
• Applying benchmark results to real-world engineering design problems, as referenced in the description.

Strengths

• Benchmark functions are from established CEC 2005 and CEC 2017 suites.
• Algorithm performance was validated using statistical procedures like Holm's post-hoc test (p < 0.05).
• Dataset is licensed under CC-BY-4.0, permitting open sharing and modification.

Limitations

• Dataset is very small (5.5 KB), indicating limited scope.
• 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

Likely compiled or generated for the FCO algorithm study.

Freshness

Last updated 2026-04-15 18:08:09