results.zip (2.7 GB)
Do Sophisticated Evolutionary Algorithms Perform Better than Simple Ones?
datasetposted on 19.01.2021, 11:40 by Michael Foster, Matthew Hughes, George O'Brien, Pietro Oliveto, James Pyle, Dirk Sudholt, James Williams
Our investigation aims to bridge the gap between theoretical and practical evolutionary algorithms. We compared the performance of a wide range of theory-driven EAs, from bare-bones algorithms like the (1+1) EA, a (2+1) GA and simple population-based algorithms to more sophisticated ones like the (1+(λ,λ)) GA and algorithms using fast (heavy-tailed) mutation operators, against sophisticated and highly effective EAs from specific applications.
EthicsThere is no personal data or any that requires ethical approval
PolicyThe data complies with the institution and funders' policies on access and sharing
Sharing and access restrictionsThe data can be shared openly
- The file formats are open or commonly used
Methodology, headings and units
- There is a readme.txt file describing the methodology, headings and units