Toward a unifying framework for evolutionary processes

Research output: Contribution to journalArticlepeer-review


  • Tiago Paixão
  • Golnaz Badkobeh
  • Nick Barton
  • Doğan Çörüş
  • Duc Cuong Dang
  • Tobias Friedrich
  • Dirk Sudholt
  • Andrew M. Sutton
  • Barbora Trubenová

Colleges, School and Institutes

External organisations

  • Institute of Science and Technology
  • University of Sheffield
  • University of Nottingham
  • Hasso Plattner Institute


The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields.


Original languageEnglish
Pages (from-to)28-43
Number of pages16
JournalJournal of Theoretical Biology
Early online date26 Jul 2015
Publication statusPublished - 21 Oct 2015