A small world algorithm for high-dimensional function optimization

Xiaohu Li; Jinhua Zhang; Sunan Wang; Maolin Li; Kunpeng Li

doi:10.1109/CIRA.2009.5423233

A small world algorithm for high-dimensional function optimization

Xiaohu Li
, Jinhua Zhang
, Sunan Wang
, Maolin Li
, Kunpeng Li

School of Mechanical Engineering

Xi'an Jiaotong University

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

10 Scopus citations

Abstract

In this paper, we describe a new small world optimization algorithm for obtaining satisfactory solution for high-dimensional function. Based on the small world phenomenon which is revealed in Milgram's sociological experiment, some operators with decimal-coding strategy are proposed, and then an "imitated society" decimal-coding small world optimization algorithm (DSWOA) is designed to solve high-dimensional function optimization. Compared with the corresponding evolution algorithms, such as orthogonal genetic algorithm with quantization (OGA/Q), the simulation results of several benchmark functions with high dimension show that DSWOA can acquire satisfied solution, has also a better stability, and a fast convergence rate. Therefore, it is feasible to solve high-dimensional optimization problems.

Original language	English
Pages	55-59
Number of pages	5
DOIs	https://doi.org/10.1109/CIRA.2009.5423233
State	Published - 2009
Event	2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2009 - Daejeon, Korea, Republic of Duration: 15 Dec 2009 → 18 Dec 2009

Conference

Conference	2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2009
Country/Territory	Korea, Republic of
City	Daejeon
Period	15/12/09 → 18/12/09

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10.1109/CIRA.2009.5423233

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title = "A small world algorithm for high-dimensional function optimization",

abstract = "In this paper, we describe a new small world optimization algorithm for obtaining satisfactory solution for high-dimensional function. Based on the small world phenomenon which is revealed in Milgram's sociological experiment, some operators with decimal-coding strategy are proposed, and then an {"}imitated society{"} decimal-coding small world optimization algorithm (DSWOA) is designed to solve high-dimensional function optimization. Compared with the corresponding evolution algorithms, such as orthogonal genetic algorithm with quantization (OGA/Q), the simulation results of several benchmark functions with high dimension show that DSWOA can acquire satisfied solution, has also a better stability, and a fast convergence rate. Therefore, it is feasible to solve high-dimensional optimization problems.",

author = "Xiaohu Li and Jinhua Zhang and Sunan Wang and Maolin Li and Kunpeng Li",

year = "2009",

doi = "10.1109/CIRA.2009.5423233",

language = "英语",

pages = "55--59",

note = "2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2009 ; Conference date: 15-12-2009 Through 18-12-2009",

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T1 - A small world algorithm for high-dimensional function optimization

AU - Li, Xiaohu

AU - Zhang, Jinhua

AU - Wang, Sunan

AU - Li, Maolin

AU - Li, Kunpeng

PY - 2009

Y1 - 2009

N2 - In this paper, we describe a new small world optimization algorithm for obtaining satisfactory solution for high-dimensional function. Based on the small world phenomenon which is revealed in Milgram's sociological experiment, some operators with decimal-coding strategy are proposed, and then an "imitated society" decimal-coding small world optimization algorithm (DSWOA) is designed to solve high-dimensional function optimization. Compared with the corresponding evolution algorithms, such as orthogonal genetic algorithm with quantization (OGA/Q), the simulation results of several benchmark functions with high dimension show that DSWOA can acquire satisfied solution, has also a better stability, and a fast convergence rate. Therefore, it is feasible to solve high-dimensional optimization problems.

AB - In this paper, we describe a new small world optimization algorithm for obtaining satisfactory solution for high-dimensional function. Based on the small world phenomenon which is revealed in Milgram's sociological experiment, some operators with decimal-coding strategy are proposed, and then an "imitated society" decimal-coding small world optimization algorithm (DSWOA) is designed to solve high-dimensional function optimization. Compared with the corresponding evolution algorithms, such as orthogonal genetic algorithm with quantization (OGA/Q), the simulation results of several benchmark functions with high dimension show that DSWOA can acquire satisfied solution, has also a better stability, and a fast convergence rate. Therefore, it is feasible to solve high-dimensional optimization problems.

UR - https://www.scopus.com/pages/publications/77951168411

U2 - 10.1109/CIRA.2009.5423233

DO - 10.1109/CIRA.2009.5423233

M3 - 论文

AN - SCOPUS:77951168411

SP - 55

EP - 59

T2 - 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2009

Y2 - 15 December 2009 through 18 December 2009

ER -

A small world algorithm for high-dimensional function optimization

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