Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm

Tian Li Yu; David E. Goldberg; Ali A. Yassine; Ying Ping Chen

Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm

Tian Li Yu, David E. Goldberg, Ali A. Yassine, Ying Ping Chen

Department of Systems Engineering

University of Illinois at Urbana-Champaign

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

38 Scopus citations

Abstract

This paper proposes a dependency structure matrix driven genetic algorithm (DSMDGA) which utilizes the dependency structure matrix clustering to extract building block (BB) information and use the information to accomplish BB-wise crossover. Three cases: tight, loose, and random linkage, are tested on both a DSMDGA and a simple genetic algorithm (SGA). Experiments showed that the DSMDGA is able to correctly identify BBs and outperforms a SGA by using the extracted BB information.

Original language	English
Pages	327-332
Number of pages	6
State	Published - 2003
Event	Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference - St. Louis, MO., United States Duration: 2 Nov 2003 → 5 Nov 2003

Conference

Conference	Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference
Country/Territory	United States
City	St. Louis, MO.
Period	2/11/03 → 5/11/03

Cite this

Yu, T. L., Goldberg, D. E., Yassine, A. A., & Chen, Y. P. (2003). Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm. 327-332. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

Yu, Tian Li ; Goldberg, David E. ; Yassine, Ali A. et al. / Genetic algorithm design inspired by organizational theory : Pilot study of dependency structure matrix driven genetic algorithm. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.6 p.

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title = "Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm",

abstract = "This paper proposes a dependency structure matrix driven genetic algorithm (DSMDGA) which utilizes the dependency structure matrix clustering to extract building block (BB) information and use the information to accomplish BB-wise crossover. Three cases: tight, loose, and random linkage, are tested on both a DSMDGA and a simple genetic algorithm (SGA). Experiments showed that the DSMDGA is able to correctly identify BBs and outperforms a SGA by using the extracted BB information.",

author = "Yu, \{Tian Li\} and Goldberg, \{David E.\} and Yassine, \{Ali A.\} and Chen, \{Ying Ping\}",

year = "2003",

language = "English",

pages = "327--332",

note = "Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference ; Conference date: 02-11-2003 Through 05-11-2003",

}

Yu, TL, Goldberg, DE, Yassine, AA & Chen, YP 2003, 'Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm', Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States, 2/11/03 - 5/11/03 pp. 327-332.

Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm. / Yu, Tian Li; Goldberg, David E.; Yassine, Ali A. et al.
2003. 327-332 Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

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

TY - CONF

T1 - Genetic algorithm design inspired by organizational theory

T2 - Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference

AU - Yu, Tian Li

AU - Goldberg, David E.

AU - Yassine, Ali A.

AU - Chen, Ying Ping

PY - 2003

Y1 - 2003

N2 - This paper proposes a dependency structure matrix driven genetic algorithm (DSMDGA) which utilizes the dependency structure matrix clustering to extract building block (BB) information and use the information to accomplish BB-wise crossover. Three cases: tight, loose, and random linkage, are tested on both a DSMDGA and a simple genetic algorithm (SGA). Experiments showed that the DSMDGA is able to correctly identify BBs and outperforms a SGA by using the extracted BB information.

AB - This paper proposes a dependency structure matrix driven genetic algorithm (DSMDGA) which utilizes the dependency structure matrix clustering to extract building block (BB) information and use the information to accomplish BB-wise crossover. Three cases: tight, loose, and random linkage, are tested on both a DSMDGA and a simple genetic algorithm (SGA). Experiments showed that the DSMDGA is able to correctly identify BBs and outperforms a SGA by using the extracted BB information.

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M3 - Paper

AN - SCOPUS:2442538832

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EP - 332

Y2 - 2 November 2003 through 5 November 2003

ER -

Yu TL, Goldberg DE, Yassine AA, Chen YP. Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm. 2003. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm

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Conference

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