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BIBTEX RIS

Analyzing Genetic Algorithm with Game Theory and Adjusted Crossover Approach on Engineering Problems

2015; Springer Nature; Linguagem: Inglês

10.1007/978-3-319-27221-4_15

ISSN

2194-5357

Autores

Edson Koiti Kudo Yasojima, Oliveira Júnior, Otávio Noura Teixeira, Rodrigo Lisbôa Pereira, Marco Antônio Florenzano Mollinetti,

Tópico(s)

Advanced Multi-Objective Optimization Algorithms

Resumo

This paper has the purpose to show game theory (GT) applied to genetic algorithms (GA) as a new type of interaction between individuals of GA. The game theory increases the exploration potential of the genetic algorithm by changing the fitness with social interaction between individuals, avoiding the algorithm to fall in a local optimum. To increase the exploitation potential of this approach, this work will present the adjusted crossover operator and compare results to other crossover methods.

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