Summary: Genetic Algorithms in Optimization:
Better than Random Search? \Lambda
Jos'e Nelson Amaral, Ph.D.
amaral@ee.pucrs.br
http://www.ee.pucrs.br/¸amaral
Adalberto Teixeira Castelo Neto
castelo@ee.pucrs.br
http://www.ee.pucrs.br/¸castelo
Alessandro Val'erio Dias
dias@ee.pucrs.br
Programa de P'os­Gradua¸c~ao em Engenharia El'etrica
Pontif'icia Universidade Cat'olica do Rio Grande do Sul
90619­900 ­ Porto Alegre ­ RS ­ Brasil
Abstract
In this paper we show that bit strings are sel­
dom the representation of choice for individu­
als in Genetic Algorithms and that genetic op­
erators must be tailored to each specific prob­
lem. We use simple functions to compare the
performance of bit string representation with

Source: Amaral, José Nelson - Department of Computing Science, University of Alberta

Collections: Computer Technologies and Information Sciences