Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning

Yiǧit Karpat; Tuǧrul Özel

Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning

Yiǧit Karpat, Tuǧrul Özel

Engn - Industrial Engineering

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS). The results showed that particle swarm optimization is an effective method for solving multi-objective optimization problems, and an integrated system of neural networks and swarm intelligence can be used in solving complex machining optimization problems.

Original language	English (US)
Title of host publication	Transactions of the North American Manufacturing Research Institute of SME 2006 - Papers Presented at NAMRC 34
Pages	611-618
Number of pages	8
State	Published - 2006
Event	34th North American Manufacturing Research Conference - Milwaukee, WI, United States Duration: May 23 2006 → May 26 2006

Publication series

Name	Transactions of the North American Manufacturing Research Institute of SME
Volume	34

Other

Other	34th North American Manufacturing Research Conference
Country/Territory	United States
City	Milwaukee, WI
Period	5/23/06 → 5/26/06

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

Keywords

Multi-objective optimization
Neural networks and hard turning
Particle swarm optimization

Cite this

@inproceedings{bae5afd9c3fd400bb2c3a5ffb3c18e2a,

title = "Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning",

abstract = "In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS). The results showed that particle swarm optimization is an effective method for solving multi-objective optimization problems, and an integrated system of neural networks and swarm intelligence can be used in solving complex machining optimization problems.",

keywords = "Multi-objective optimization, Neural networks and hard turning, Particle swarm optimization",

author = "Yiǧit Karpat and Tuǧrul {\"O}zel",

year = "2006",

language = "English (US)",

isbn = "0872638480",

series = "Transactions of the North American Manufacturing Research Institute of SME",

pages = "611--618",

booktitle = "Transactions of the North American Manufacturing Research Institute of SME 2006 - Papers Presented at NAMRC 34",

note = "34th North American Manufacturing Research Conference ; Conference date: 23-05-2006 Through 26-05-2006",

}

Karpat, Y & Özel, T 2006, Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning. in Transactions of the North American Manufacturing Research Institute of SME 2006 - Papers Presented at NAMRC 34. Transactions of the North American Manufacturing Research Institute of SME, vol. 34, pp. 611-618, 34th North American Manufacturing Research Conference, Milwaukee, WI, United States, 5/23/06.

Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning. / Karpat, Yiǧit; Özel, Tuǧrul.

Transactions of the North American Manufacturing Research Institute of SME 2006 - Papers Presented at NAMRC 34. 2006. p. 611-618 (Transactions of the North American Manufacturing Research Institute of SME; Vol. 34).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning

AU - Karpat, Yiǧit

AU - Özel, Tuǧrul

PY - 2006

Y1 - 2006

N2 - In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS). The results showed that particle swarm optimization is an effective method for solving multi-objective optimization problems, and an integrated system of neural networks and swarm intelligence can be used in solving complex machining optimization problems.

AB - In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS). The results showed that particle swarm optimization is an effective method for solving multi-objective optimization problems, and an integrated system of neural networks and swarm intelligence can be used in solving complex machining optimization problems.

KW - Multi-objective optimization

KW - Neural networks and hard turning

KW - Particle swarm optimization

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M3 - Conference contribution

SN - 0872638480

SN - 9780872638488

T3 - Transactions of the North American Manufacturing Research Institute of SME

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EP - 618

BT - Transactions of the North American Manufacturing Research Institute of SME 2006 - Papers Presented at NAMRC 34

T2 - 34th North American Manufacturing Research Conference

Y2 - 23 May 2006 through 26 May 2006

ER -

Swarm-intelligent neural network system (SINNS) based multi-objective optimization of hard turning

Abstract

Publication series

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ASJC Scopus subject areas

Keywords

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