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Article

A study of fitness distance correlation as a difficulty measure in genetic programming.

Evolutionary computation - 1 Jan 2005

Tomassini Marco, Vanneschi Leonardo, Collard Philippe, Clergue Manuel

Abstract excerpt

We present an approach to genetic programming difficulty based on a statistical study of program fitness landscapes. The fitness distance correlation is used as an indicator of problem hardness and we empirically show that such a statistic is adequate in nearly all cases studied here. However, fitness distance correlation has some known problems and these are investigated by constructing an artificial landscape...

Topics

Algorithms
Animals
Biological Evolution
Computational Biology
Computer Simulation
Genetics, Population
Humans
Mathematical Computing
Mathematics
Models, Biological
Models, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Models, Statistical

Mutation

Selection, Genetic

Software

Source

Identifiers

PMID: 15969901
DOI: 10.1162/1063656054088549

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

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