Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms

Shane Lee; Hefin Rowlands

Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms

Shane Lee^*, Hefin Rowlands

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Genetic algorithms that utilise floating point-encoded chromosomes instead of the traditional binary or Gary code have become wide spread in recent years. This paper introduces new floatingpoint crossover and mutation operators for such genetic algorithms. The operators are derived from examining the implicit constraints that traditional binary crossover and mutation operators impose on the values of the parameters being affected. It is shown by an example that a genetic algorithm using these operators does converge and they should be considered for general use in floating-point genetic algorithms.

Original language	English
Title of host publication	Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005
Pages	103-108
Number of pages	6
Publication status	Published - 1 Dec 2005
Event	19th European Conference on Modelling and Simulation, ECMS 2005 - Riga, Latvia Duration: 1 Jun 2005 → 4 Jun 2005

Publication series

Name	Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005

Conference

Conference	19th European Conference on Modelling and Simulation, ECMS 2005
Country/Territory	Latvia
City	Riga
Period	1/06/05 → 4/06/05

Keywords

Floating-point encoded
Genetic algorithm
Real encoded

Cite this

@inproceedings{80da2aa9b174494c96246ae8fe3260e4,

title = "Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms",

abstract = "Genetic algorithms that utilise floating point-encoded chromosomes instead of the traditional binary or Gary code have become wide spread in recent years. This paper introduces new floatingpoint crossover and mutation operators for such genetic algorithms. The operators are derived from examining the implicit constraints that traditional binary crossover and mutation operators impose on the values of the parameters being affected. It is shown by an example that a genetic algorithm using these operators does converge and they should be considered for general use in floating-point genetic algorithms.",

keywords = "Floating-point encoded, Genetic algorithm, Real encoded",

author = "Shane Lee and Hefin Rowlands",

year = "2005",

month = dec,

day = "1",

language = "English",

isbn = "1842331124",

series = "Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005",

pages = "103--108",

booktitle = "Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005",

note = "19th European Conference on Modelling and Simulation, ECMS 2005 ; Conference date: 01-06-2005 Through 04-06-2005",

}

Lee, S & Rowlands, H 2005, Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms. in Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005. Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005, pp. 103-108, 19th European Conference on Modelling and Simulation, ECMS 2005, Riga, Latvia, 1/06/05.

Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms. / Lee, Shane; Rowlands, Hefin.

Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005. 2005. p. 103-108 (Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms

AU - Lee, Shane

AU - Rowlands, Hefin

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Genetic algorithms that utilise floating point-encoded chromosomes instead of the traditional binary or Gary code have become wide spread in recent years. This paper introduces new floatingpoint crossover and mutation operators for such genetic algorithms. The operators are derived from examining the implicit constraints that traditional binary crossover and mutation operators impose on the values of the parameters being affected. It is shown by an example that a genetic algorithm using these operators does converge and they should be considered for general use in floating-point genetic algorithms.

AB - Genetic algorithms that utilise floating point-encoded chromosomes instead of the traditional binary or Gary code have become wide spread in recent years. This paper introduces new floatingpoint crossover and mutation operators for such genetic algorithms. The operators are derived from examining the implicit constraints that traditional binary crossover and mutation operators impose on the values of the parameters being affected. It is shown by an example that a genetic algorithm using these operators does converge and they should be considered for general use in floating-point genetic algorithms.

KW - Floating-point encoded

KW - Genetic algorithm

KW - Real encoded

M3 - Conference contribution

AN - SCOPUS:84863028982

SN - 1842331124

SN - 9781842331125

T3 - Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005

SP - 103

EP - 108

BT - Simulation in Wider Europe - 19th European Conference on Modelling and Simulation, ECMS 2005

T2 - 19th European Conference on Modelling and Simulation, ECMS 2005

Y2 - 1 June 2005 through 4 June 2005

ER -

Introducing the swingometer crossover and mutation operators for floating-point encoded genetic algorithms

Abstract

Publication series

Conference

Keywords

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