Skip to Main Content
ASME Press Select Proceedings

Intelligent Engineering Systems through Artificial Neural Networks, Volume 16

Editor
Cihan H. Dagli
Cihan H. Dagli
Search for other works by this author on:
Anna L. Buczak
Anna L. Buczak
Search for other works by this author on:
David L. Enke
David L. Enke
Search for other works by this author on:
Mark Embrechts
Mark Embrechts
Search for other works by this author on:
Okan Ersoy
Okan Ersoy
Search for other works by this author on:
ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006

This paper seeks to determine the feasibility of using fuzzy concepts in conjunction with genetic algorithms in order to solve multi-objective decision making problems. The domain chosen is the area of single machine scheduling. Another focus of this research is to test the feasibility of gene detection strategies to perform block crossover during the evolution cycle of the genetic algorithm. During block crossover, the good gene segments from the parent chromosomes are preserved in the child chromosomes. Several problems with known optimal solutions for non-zero ready times are tested using the proposed method and results are reported. The results indicate that the proposed method found the optimal solution in 20-job category with high frequency.

This content is only available via PDF.
Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal