Multimodal Benchmark Functions for Metaheuristic Algorithm Testing

A set of benchmark functions used to evaluate the Felis Catus Optimization (FCO) metaheuristic algorithm. The dataset includes results from experiments on the CEC 2005 and CEC 2017 benchmark suites and three real-world engineering design problems. It was created by Mohammad Salehi and last updated on April 15, 2026.

Use Cases

• Benchmarking new optimization algorithms based on performance on CEC 2005 and CEC 2017 suites.
• Evaluating algorithm convergence and resilience against premature stagnation using the provided test results.
• Applying optimization techniques to real-world engineering design problems, as demonstrated in the study.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Results are validated with statistical procedures including Holm's post-hoc test and critical-difference analysis.
• Performance is demonstrated on three real-world engineering problems, showing low result variance.

Limitations

• Row count and specific column definitions are unknown, limiting suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset's scope is limited to the specific benchmark functions and problems used in the FCO study.

Provenance

Source

Mohammad Salehi via figshare

Collection Method

Generated from experiments evaluating the Felis Catus Optimization algorithm.

Freshness

Last updated 2026-04-15 18:08:07