Abstract
Evolutionary algorithms are a common probabilistic optimization method based on the model of natural evolution. One important operator in these algorithms is the selection scheme, for which in this paper a new description model, based on fitness distributions, is introduced. With this, a mathematical analysis of tournament selection, truncation selection, ranking selection, and exponential ranking selection is carried out that allows an exact prediction of the fitness values after selection. The correspondence of binary tournament selection and ranking selection in the expected fitness distribution is proved. Furthermore, several properties of selection schemes are derived (selection intensity, selection variance, loss of diversity), and the three selection schemes are compared using these properties.
Keywords
Fitness proportionate selectionTournament selectionTruncation selectionSelection (genetic algorithm)Ranking (information retrieval)Mathematical optimizationDisruptive selectionEvolutionary algorithmMathematicsComputer scienceProbabilistic logicAlgorithmNatural selectionMachine learningArtificial intelligenceFitness functionGenetic algorithm
Affiliated Institutions
Related Publications
Genetic Algorithms in Search, Optimization and Machine Learning
David Goldberg's Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent ...
A modified particle swarm optimizer
Evolutionary computation techniques, genetic algorithms, evolutionary strategies and genetic programming are motivated by the evolution of nature. A population of individuals, w...
Handbook of Genetic Algorithms
This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems. The first objective is tackled by the editor, Lawrence Davis. Th...
A new optimizer using particle swarm theory
The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently develope...
Positive Natural Selection in the Human Lineage
Positive natural selection is the force that drives the increase in prevalence of advantageous traits, and it has played a central role in our development as a species. Until re...
Publication Info
- Year
- 1996
- Type
- article
- Volume
- 4
- Issue
- 4
- Pages
- 361-394
- Citations
- 574
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
574
OpenAlex
Cite This
Tobias Blickle,
Lothar Thiele
(1996).
A Comparison of Selection Schemes Used in Evolutionary Algorithms.
Evolutionary Computation
, 4
(4)
, 361-394.
https://doi.org/10.1162/evco.1996.4.4.361
Identifiers
- DOI
- 10.1162/evco.1996.4.4.361