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Author(s): Carlos C. António
Title: Evolutionary search based on aged structured population and selfish gene theory
Issue Date: 2010
Abstract: In this paper it is analysed the application of the selfish gene theory using a fusion of concepts proposed in memeticalgorithms and selfish gene algorithms. The selfish gene ideas are applied to hierarchical genetic algorithm (HGA)with age structure previously developed by the author. First of all it is analysed the memetic features mainly thelearning procedures of the HGA. Secondly, the selfish gene theory (SG) is applied to age structured populationaiming to improve the performance of HGA. The evolution of the age structured population is based on the selfishgene theory where the population can be simply seen as a pool of genes and individual genes fight for the samespot in the chromosome of the genotype. The new operator is denoted by Age parameterised Selfish Gene (ApSG)crossover. It is based on a pseudo-crossover scheme with modified Mating Selection Mechanism and OffspringGeneration Mechanism influenced by best alleles in the age-structured virtual population. This population evolvesto get the best solution using the interaction between the frequencies of the alleles in a same gene group and bychanging these frequencies according to the corresponding fitness of individuals. The offspring individuals areinserted into age-structured virtual and current populations according to Lamarckian learning. Finally it isdiscussed the effects of different learning procedures in the HGA-SG approaches.
Subject: Ciências Tecnológicas, Outras ciências da engenharia e tecnologias
Technological sciences, Other engineering and technologies
Scientific areas: Ciências da engenharia e tecnologias::Outras ciências da engenharia e tecnologias
Engineering and technology::Other engineering and technologies
Source: EngOpt 2010
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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