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 |
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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 |
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Country/Territory | United States |
City | St. Louis, MO. |
Period | 2/11/03 → 5/11/03 |