Jumping gene genetic algorithm and its applications in controller design

J. J. Yin; Wallace Tang; K. F. Man

doi:10.1109/ISIE.2008.4677058

Jumping gene genetic algorithm and its applications in controller design

J. J. Yin
, Wallace Tang
, K. F. Man

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

In this paper, two newly-designed jumping gene (JG) operations are proposed for the enhancement of genetic algorithm (GA). Based on the recent findings on their schemata growth rates, it is recognized that JG can provide the essential diversity in a GA so as to greatly enhance its searching ability. This nature is particularly important for multi-objective problem, in which a set of Pareto solutions is expected. As demonstrated by its application on the design of Fuzzy PID controllers, JGGA is considered as an effective and reliable methodology for multi-objective designs. © 2008 IEEE.

Original language	English
Title of host publication	IEEE International Symposium on Industrial Electronics
Pages	1219-1224
DOIs	https://doi.org/10.1109/ISIE.2008.4677058
Publication status	Published - 2008
Event	2008 IEEE International Symposium on Industrial Electronics (ISIE 2008) - Cambridge, United Kingdom Duration: 30 Jun 2008 → 2 Jul 2008

Conference

Conference	2008 IEEE International Symposium on Industrial Electronics (ISIE 2008)
Place	United Kingdom
City	Cambridge
Period	30/06/08 → 2/07/08

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title = "Jumping gene genetic algorithm and its applications in controller design",

abstract = "In this paper, two newly-designed jumping gene (JG) operations are proposed for the enhancement of genetic algorithm (GA). Based on the recent findings on their schemata growth rates, it is recognized that JG can provide the essential diversity in a GA so as to greatly enhance its searching ability. This nature is particularly important for multi-objective problem, in which a set of Pareto solutions is expected. As demonstrated by its application on the design of Fuzzy PID controllers, JGGA is considered as an effective and reliable methodology for multi-objective designs. {\textcopyright} 2008 IEEE.",

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AU - Tang, Wallace

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N2 - In this paper, two newly-designed jumping gene (JG) operations are proposed for the enhancement of genetic algorithm (GA). Based on the recent findings on their schemata growth rates, it is recognized that JG can provide the essential diversity in a GA so as to greatly enhance its searching ability. This nature is particularly important for multi-objective problem, in which a set of Pareto solutions is expected. As demonstrated by its application on the design of Fuzzy PID controllers, JGGA is considered as an effective and reliable methodology for multi-objective designs. © 2008 IEEE.

AB - In this paper, two newly-designed jumping gene (JG) operations are proposed for the enhancement of genetic algorithm (GA). Based on the recent findings on their schemata growth rates, it is recognized that JG can provide the essential diversity in a GA so as to greatly enhance its searching ability. This nature is particularly important for multi-objective problem, in which a set of Pareto solutions is expected. As demonstrated by its application on the design of Fuzzy PID controllers, JGGA is considered as an effective and reliable methodology for multi-objective designs. © 2008 IEEE.

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U2 - 10.1109/ISIE.2008.4677058

DO - 10.1109/ISIE.2008.4677058

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 1424416655

SN - 9781424416653

SP - 1219

EP - 1224

BT - IEEE International Symposium on Industrial Electronics

T2 - 2008 IEEE International Symposium on Industrial Electronics (ISIE 2008)

Y2 - 30 June 2008 through 2 July 2008

ER -

Jumping gene genetic algorithm and its applications in controller design

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