Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1022692631328
Title: Sexual selection for genetic algorithms
Authors: Goh, K.S.
Lim, A. 
Rodrigues, B.
Keywords: Genetic algorithm
Scheduling
Selection
Issue Date: 2003
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
URI: http://scholarbank.nus.edu.sg/handle/10635/39027
ISSN: 02692821
DOI: 10.1023/A:1022692631328
Appears in Collections:Staff Publications

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