A modified genetic algorithm for solving nonlinear hybrid optimization problem

Minle Wang; Xiaoguang Gao; Guangbin Liu

A modified genetic algorithm for solving nonlinear hybrid optimization problem

Minle Wang, Xiaoguang Gao, Guangbin Liu

School of Electronics and Information

Rocket Force University of Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, to aim at the problem of solving nonlinear hybrid integer programming , the modified Genetic Algorithm is presented on the basis of designing new encoding scheme and genetic operators. Applied to the problem of missile effectiveness optimization in attacking group targets, the new algorithm proves to be effective and efficient.

Original language	English
Pages	2167-2170
Number of pages	4
State	Published - 2004
Event	WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings - Hangzhou, China Duration: 15 Jun 2004 → 19 Jun 2004

Conference

Conference	WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings
Country/Territory	China
City	Hangzhou
Period	15/06/04 → 19/06/04

Keywords

Genetic Algorithm
Missile
Nonlinear integer programming
Operational effectiveness
Operator

Cite this

@conference{20149bd360324c03b6ea2a85c68f59de,

title = "A modified genetic algorithm for solving nonlinear hybrid optimization problem",

abstract = "In this paper, to aim at the problem of solving nonlinear hybrid integer programming , the modified Genetic Algorithm is presented on the basis of designing new encoding scheme and genetic operators. Applied to the problem of missile effectiveness optimization in attacking group targets, the new algorithm proves to be effective and efficient.",

keywords = "Genetic Algorithm, Missile, Nonlinear integer programming, Operational effectiveness, Operator",

author = "Minle Wang and Xiaoguang Gao and Guangbin Liu",

year = "2004",

language = "英语",

pages = "2167--2170",

note = "WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings ; Conference date: 15-06-2004 Through 19-06-2004",

}

TY - CONF

T1 - A modified genetic algorithm for solving nonlinear hybrid optimization problem

AU - Wang, Minle

AU - Gao, Xiaoguang

AU - Liu, Guangbin

PY - 2004

Y1 - 2004

N2 - In this paper, to aim at the problem of solving nonlinear hybrid integer programming , the modified Genetic Algorithm is presented on the basis of designing new encoding scheme and genetic operators. Applied to the problem of missile effectiveness optimization in attacking group targets, the new algorithm proves to be effective and efficient.

AB - In this paper, to aim at the problem of solving nonlinear hybrid integer programming , the modified Genetic Algorithm is presented on the basis of designing new encoding scheme and genetic operators. Applied to the problem of missile effectiveness optimization in attacking group targets, the new algorithm proves to be effective and efficient.

KW - Genetic Algorithm

KW - Missile

KW - Nonlinear integer programming

KW - Operational effectiveness

KW - Operator

UR - http://www.scopus.com/inward/record.url?scp=4444371625&partnerID=8YFLogxK

M3 - 论文

AN - SCOPUS:4444371625

SP - 2167

EP - 2170

T2 - WCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings

Y2 - 15 June 2004 through 19 June 2004

ER -

A modified genetic algorithm for solving nonlinear hybrid optimization problem

Abstract

Conference

Keywords

Other files and links

Fingerprint

Cite this