The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

R Cavill; S Smith; A Tyrrell

The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

Electronic Engineering

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

Abstract

This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both.

Original language	English
Title of host publication	2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS
Place of Publication	NEW YORK
Publisher	IEEE
Pages	935-941
Number of pages	7
ISBN (Print)	0-7803-9363-5
Publication status	Published - 2005
Event	IEEE Congress on Evolutionary Computation - Edinburgh Duration: 2 Sep 2005 → 5 Sep 2005

Conference

Conference	IEEE Congress on Evolutionary Computation
City	Edinburgh
Period	2/09/05 → 5/09/05

Cite this

@inproceedings{6dd4186ac46a4329ab35747cf83fc477,

title = "The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems",

abstract = "This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both.",

author = "R Cavill and S Smith and A Tyrrell",

year = "2005",

language = "English",

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pages = "935--941",

booktitle = "2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS",

publisher = "IEEE",

address = "United States",

note = "IEEE Congress on Evolutionary Computation ; Conference date: 02-09-2005 Through 05-09-2005",

}

Cavill, R, Smith, S & Tyrrell, A 2005, The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems. in 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS. IEEE, NEW YORK, pp. 935-941, IEEE Congress on Evolutionary Computation, Edinburgh, 2/09/05.

The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems. / Cavill, R; Smith, S ; Tyrrell, A.

2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS. NEW YORK : IEEE, 2005. p. 935-941.

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

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T1 - The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

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AU - Smith, S

AU - Tyrrell, A

PY - 2005

Y1 - 2005

N2 - This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both.

AB - This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both.

M3 - Conference contribution

SN - 0-7803-9363-5

SP - 935

EP - 941

BT - 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS

PB - IEEE

CY - NEW YORK

T2 - IEEE Congress on Evolutionary Computation

Y2 - 2 September 2005 through 5 September 2005

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