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Chapter

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Title

Revealing the Inner Dynamics of Evolutionary Algorithms with Convection Selection

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • evolutionary algorithms
  • evolutionary dynamics
  • design and analysis of algorithms
  • convection selection
Abstract

EN Evolutionary algorithms are stochastic algorithms so they tend to find different solutions when run repeatedly. However, it is not just the solutions that vary – the very dynamics of the search that led to finding these solutions are likely to differ as well. It is especially in the algorithms with complex population structures – such as convection selection where a population is divided into subpopulations according to fitness values – where an opportunity for highly diverse dynamics arises. This work investigates the way evolutionary dynamics of subpopulations influence the performance of evolutionary algorithms with convection selection. We emploi a demanding task of evolutionary design of 3D structures to analyze the relation between the properties of the optimization task and the features of the evolutionary process. Based on this analysis, we identify the mechanisms that influence the performance of convection selection, and suggest ways to improve this selection scheme.

Date of online publication

24.07.2023

Pages (from - to)

491 - 494

DOI

10.1145/3583133.3590708

URL

https://dl.acm.org/doi/pdf/10.1145/3583133.3590708

Book

GECCO '23 Companion : Proceedings of the Companion Conference on Genetic and Evolutionary Computation, July 15-19, 2023, Lisbon, Portugal

Presented on

GECCO '23 Genetic and Evolutionary Computation Conference, 15-19.07.2023, Lisbon, Portugal

Ministry points / chapter

20

Ministry points / conference (CORE)

140

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