Please use this identifier to cite or link to this item:
|Title:||Sexual selection for genetic algorithms|
|Source:||Goh, K.S., Lim, A., Rodrigues, B. (2003). Sexual selection for genetic algorithms. Artificial Intelligence Review 19 (2) : 123-152. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1022692631328|
|Abstract:||Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling functions. We also examine common problems and solution methods for such selection schemes. We then propose a new selection scheme inspired by sexual selection principles through female choice selection, and compare the performance of this new scheme with commonly used selection methods in solving some well-known problems including the Royal Road Problem, the Open Shop Scheduling Problem and the Job Shop Scheduling Problem.|
|Source Title:||Artificial Intelligence Review|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 6, 2017
WEB OF SCIENCETM
checked on Nov 22, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.