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Modelling the Dynamics of a Steady State Genetic Algorithm

Modelling the Dynamics of a Steady State Genetic Algorithm
Modelling the Dynamics of a Steady State Genetic Algorithm
A comparison is made between the dynamics of steady state and generational genetic algorithms using the statistical mechanics approach developed by Prugel-Bennett, Shapiro and Rattray. It is shown that the loss of variance of the population under steady state selection - genetic drift - occurs at twice the rate of generational selection. By considering a simple ones counting problem with selection and mutation, it is shown that, with weak selection, the steady state genetic algorithm can reproduce the dynamics of the generational genetic algorithm at half the computational cost in terms of function evaluations.
1-55860-559-2
57-68
Springer
Rogers, A.
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Prügel-Bennett, A.
b107a151-1751-4d8b-b8db-2c395ac4e14e
Banzhaf, W.
Reeves, C.
Rogers, A.
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Prügel-Bennett, A.
b107a151-1751-4d8b-b8db-2c395ac4e14e
Banzhaf, W.
Reeves, C.

Rogers, A. and Prügel-Bennett, A. (1999) Modelling the Dynamics of a Steady State Genetic Algorithm. In, Banzhaf, W. and Reeves, C. (eds.) Foundations of Genetic Algorithms 5. Foundations of Genetic Algorithms - 5 (01/09/99) Springer, pp. 57-68.

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Abstract

A comparison is made between the dynamics of steady state and generational genetic algorithms using the statistical mechanics approach developed by Prugel-Bennett, Shapiro and Rattray. It is shown that the loss of variance of the population under steady state selection - genetic drift - occurs at twice the rate of generational selection. By considering a simple ones counting problem with selection and mutation, it is shown that, with weak selection, the steady state genetic algorithm can reproduce the dynamics of the generational genetic algorithm at half the computational cost in terms of function evaluations.

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Published date: September 1999
Additional Information: Address: San Francisco
Venue - Dates: Foundations of Genetic Algorithms - 5, 1999-09-01
Organisations: Agents, Interactions & Complexity, Southampton Wireless Group

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Local EPrints ID: 250451
URI: https://eprints.soton.ac.uk/id/eprint/250451
ISBN: 1-55860-559-2
PURE UUID: 5232093d-bbdf-4ab1-972a-61674259e73c

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Date deposited: 17 Aug 1999
Last modified: 18 Jul 2019 16:07

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Contributors

Author: A. Rogers
Author: A. Prügel-Bennett
Editor: W. Banzhaf
Editor: C. Reeves

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