Variable length encoded genetic algorithm for optimal electrical distribution network routing

James R.E. Fletcher; Tyrone Fernando; Herbert H.C. Iu; Mark Reynolds; Shervin Fani

doi:10.1109/SSCI.2017.8285169

Variable length encoded genetic algorithm for optimal electrical distribution network routing

James R.E. Fletcher, Tyrone Fernando, Herbert H.C. Iu, Mark Reynolds, Shervin Fani

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

2 Citations (Scopus)

Abstract

We describe a genetic algorithm approach to the practical problem of electrical distribution network routing through areas of relatively sparse population. The objective is evaluated through minimizing the total network investment cost, comprised of capital and operational costs, over the selected time period. The genetic algorithm benefits from a variable length genome, a number of interesting mutations based on Steiner points and careful management of population diversity. Evaluation on a real network benchmark shows improved performance to previous approaches under the assumption of free path traversal, and warrants further investigation.

Original language	English
Title of host publication	2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Place of Publication	USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-8
Number of pages	8
Volume	2018-January
ISBN (Electronic)	9781538627259
DOIs	https://doi.org/10.1109/SSCI.2017.8285169
Publication status	Published - 2 Feb 2018
Event	2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Honolulu, United States Duration: 27 Nov 2017 → 1 Dec 2017

Conference

Conference	2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017
Country/Territory	United States
City	Honolulu
Period	27/11/17 → 1/12/17

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10.1109/SSCI.2017.8285169

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Fletcher, J. R. E., Fernando, T., Iu, H. H. C., Reynolds, M., & Fani, S. (2018). Variable length encoded genetic algorithm for optimal electrical distribution network routing. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (Vol. 2018-January, pp. 1-8). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SSCI.2017.8285169

@inproceedings{243ebc72bee54bb1ac7496c4f5120d27,

title = "Variable length encoded genetic algorithm for optimal electrical distribution network routing",

abstract = "We describe a genetic algorithm approach to the practical problem of electrical distribution network routing through areas of relatively sparse population. The objective is evaluated through minimizing the total network investment cost, comprised of capital and operational costs, over the selected time period. The genetic algorithm benefits from a variable length genome, a number of interesting mutations based on Steiner points and careful management of population diversity. Evaluation on a real network benchmark shows improved performance to previous approaches under the assumption of free path traversal, and warrants further investigation.",

keywords = "Genetic algorithm (GA), Power distribution planning (PDP), Steiner trees",

author = "Fletcher, {James R.E.} and Tyrone Fernando and Iu, {Herbert H.C.} and Mark Reynolds and Shervin Fani",

year = "2018",

month = feb,

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doi = "10.1109/SSCI.2017.8285169",

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booktitle = "2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 ; Conference date: 27-11-2017 Through 01-12-2017",

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Fletcher, JRE, Fernando, T , Iu, HHC , Reynolds, M & Fani, S 2018, Variable length encoded genetic algorithm for optimal electrical distribution network routing. in 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings. vol. 2018-January, IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 1-8, 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017, Honolulu, United States, 27/11/17. https://doi.org/10.1109/SSCI.2017.8285169

Variable length encoded genetic algorithm for optimal electrical distribution network routing. / Fletcher, James R.E.; Fernando, Tyrone ; Iu, Herbert H.C. et al.

2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings. Vol. 2018-January USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 1-8.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

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AU - Reynolds, Mark

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N2 - We describe a genetic algorithm approach to the practical problem of electrical distribution network routing through areas of relatively sparse population. The objective is evaluated through minimizing the total network investment cost, comprised of capital and operational costs, over the selected time period. The genetic algorithm benefits from a variable length genome, a number of interesting mutations based on Steiner points and careful management of population diversity. Evaluation on a real network benchmark shows improved performance to previous approaches under the assumption of free path traversal, and warrants further investigation.

AB - We describe a genetic algorithm approach to the practical problem of electrical distribution network routing through areas of relatively sparse population. The objective is evaluated through minimizing the total network investment cost, comprised of capital and operational costs, over the selected time period. The genetic algorithm benefits from a variable length genome, a number of interesting mutations based on Steiner points and careful management of population diversity. Evaluation on a real network benchmark shows improved performance to previous approaches under the assumption of free path traversal, and warrants further investigation.

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KW - Power distribution planning (PDP)

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VL - 2018-January

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BT - 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - USA

T2 - 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017

Y2 - 27 November 2017 through 1 December 2017

ER -

Fletcher JRE, Fernando T , Iu HHC , Reynolds M, Fani S. Variable length encoded genetic algorithm for optimal electrical distribution network routing. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings. Vol. 2018-January. USA: IEEE, Institute of Electrical and Electronics Engineers. 2018. p. 1-8 https://doi.org/10.1109/SSCI.2017.8285169

Variable length encoded genetic algorithm for optimal electrical distribution network routing

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