Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

14

GECCO
2004
Springer

favoriteEmaildiscussreport

81views Optimization» more GECCO 2004»

On the Choice of the Population Size

13 years 10 months ago

On the Choice of the Population Size

Download www.cs.york.ac.uk

Abstract. Evolutionary Algorithms (EAs) are population-based randomized optimizers often solving problems quite successfully. Here, the focus is on the possible eﬀects of changing the parent population size. Therefore, new functions are presented where for a simple mutationbased EA even a decrease of the population size by one leads from an eﬃcient optimization to an enormous running time with an overwhelming probability. This is proven rigorously for all feasible population sizes. In order to obtain these results, new methods for the analysis of the EA are developed.

Tobias Storch

Real-time Traffic

GECCO 2004 | Parent Population Size | Population Sizes | Population-based Randomized Optimizers |

claim paper

Related Content

» Investigating the LocalMetaModel CMAES for Large Population Sizes

» ParameterLess Hierarchical BOA

» Expected Allele Coverage and the Role of Mutation in Genetic Algorithms

» A note on the population based incremental learning with infinite population size

» A Model of Human Mate Choice with Courtship That Predicts Population Patterns

» Large Populations Are Not Always The Best Choice In Genetic Programming

» Shape versus Size Improved Understanding of the Morphology of Brain Structures

» A New Selection Ratio for Large Population Sizes

» Genetic programming optimal population sizes for varying complexity problems

Post Info
More Details (n/a)

Added	01 Jul 2010
Updated	01 Jul 2010
Type	Conference
Year	2004
Where	GECCO
Authors	Tobias Storch

Comments (0)