Enhancement of multiobjective search : A jumping-genes approach

J. J. YIN; S. H. YEUNG; Wallace K. S. TANG; K. F. MAN; S. KWONG

doi:10.1109/ISIE.2007.4374889

Enhancement of multiobjective search : A jumping-genes approach

J. J. YIN, S. H. YEUNG, Wallace K. S. TANG, K. F. MAN, S. KWONG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

2 Citations (Scopus)

Abstract

Inspired by the gene transposition in biological genome, recently, a new evolutionary computing algorithm has been developed for optimization. It consists of two newly designed operations: copy-and-paste and cut-and-paste, which have been proven mathematically on the basis of Schema theory. In this paper, their uniqueness for balancing the exploration and exploitation searching effect is explained. In the meantime, the enhancement of searching efficiency for the multiobjective problems is demonstrated. Its ability is further reinforced by a real world application for a microstrip patch antennae design. The obtained results indicated that this new algorithm is indeed beneficial for gaining a much improved non-dominated solutions front as compared with those derived from the conventional method. ©2007 IEEE.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE International Symposium on Industrial Electronics
Publisher	IEEE
Pages	1855-1858
Number of pages	5
ISBN (Print)	9781424407545
DOIs	https://doi.org/10.1109/ISIE.2007.4374889
Publication status	Published - 2007
Externally published	Yes
Event	2007 IEEE International Symposium on Industrial Electronics - Centro Cultural and Centro Social Caixanova, Vigo, Spain Duration: 4 Jun 2007 → 7 Jun 2007

Symposium

Symposium	2007 IEEE International Symposium on Industrial Electronics
Abbreviated title	ISIE 2007
Country/Territory	Spain
City	Vigo
Period	4/06/07 → 7/06/07

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10.1109/ISIE.2007.4374889

Cite this

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title = "Enhancement of multiobjective search : A jumping-genes approach",

abstract = "Inspired by the gene transposition in biological genome, recently, a new evolutionary computing algorithm has been developed for optimization. It consists of two newly designed operations: copy-and-paste and cut-and-paste, which have been proven mathematically on the basis of Schema theory. In this paper, their uniqueness for balancing the exploration and exploitation searching effect is explained. In the meantime, the enhancement of searching efficiency for the multiobjective problems is demonstrated. Its ability is further reinforced by a real world application for a microstrip patch antennae design. The obtained results indicated that this new algorithm is indeed beneficial for gaining a much improved non-dominated solutions front as compared with those derived from the conventional method. {\textcopyright}2007 IEEE.",

author = "YIN, {J. J.} and YEUNG, {S. H.} and TANG, {Wallace K. S.} and MAN, {K. F.} and S. KWONG",

year = "2007",

doi = "10.1109/ISIE.2007.4374889",

language = "English",

isbn = "9781424407545",

pages = "1855--1858",

booktitle = "Proceedings of the 2007 IEEE International Symposium on Industrial Electronics",

publisher = "IEEE",

note = "2007 IEEE International Symposium on Industrial Electronics<br/>, ISIE 2007 ; Conference date: 04-06-2007 Through 07-06-2007",

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T1 - Enhancement of multiobjective search : A jumping-genes approach

AU - YIN, J. J.

AU - YEUNG, S. H.

AU - TANG, Wallace K. S.

AU - MAN, K. F.

AU - KWONG, S.

PY - 2007

Y1 - 2007

N2 - Inspired by the gene transposition in biological genome, recently, a new evolutionary computing algorithm has been developed for optimization. It consists of two newly designed operations: copy-and-paste and cut-and-paste, which have been proven mathematically on the basis of Schema theory. In this paper, their uniqueness for balancing the exploration and exploitation searching effect is explained. In the meantime, the enhancement of searching efficiency for the multiobjective problems is demonstrated. Its ability is further reinforced by a real world application for a microstrip patch antennae design. The obtained results indicated that this new algorithm is indeed beneficial for gaining a much improved non-dominated solutions front as compared with those derived from the conventional method. ©2007 IEEE.

AB - Inspired by the gene transposition in biological genome, recently, a new evolutionary computing algorithm has been developed for optimization. It consists of two newly designed operations: copy-and-paste and cut-and-paste, which have been proven mathematically on the basis of Schema theory. In this paper, their uniqueness for balancing the exploration and exploitation searching effect is explained. In the meantime, the enhancement of searching efficiency for the multiobjective problems is demonstrated. Its ability is further reinforced by a real world application for a microstrip patch antennae design. The obtained results indicated that this new algorithm is indeed beneficial for gaining a much improved non-dominated solutions front as compared with those derived from the conventional method. ©2007 IEEE.

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M3 - Conference paper (refereed)

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BT - Proceedings of the 2007 IEEE International Symposium on Industrial Electronics

PB - IEEE

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Y2 - 4 June 2007 through 7 June 2007

ER -

Enhancement of multiobjective search : A jumping-genes approach

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