Toward a unifying framework for evolutionary processes

Paixão, Tiago; Badkobeh, Golnaz; Barton, Nick; Çörüş, Doğan; Dang, Duc-Cuong; Friedrich, Tobias; Lehre, Per Kristian; Sudholt, Dirk; Sutton, Andrew M. and Trubenová, Barbora. 2015. Toward a unifying framework for evolutionary processes. Journal of Theoretical Biology, 383, pp. 28-43. ISSN 0022-5193 [Article]

1-s2.0-S0022519315003409-main.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (595kB) | Preview

Abstract or Description

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.

Item Type:


Identification Number (DOI):


Population genetics, Evolution, Evolutionary computation, Mathematical modelling

Departments, Centres and Research Units:



15 July 2015Accepted
26 July 2015Published Online
21 October 2015Published

Item ID:


Date Deposited:

05 Dec 2019 09:39

Last Modified:

10 Jun 2021 03:12

Peer Reviewed:

Yes, this version has been peer-reviewed.


View statistics for this item...

Edit Record Edit Record (login required)