Renato Simões Moreira1, Otávio Noura Teixeira2, and Roberto Célio Limão de Oliveira1
1 PPGEE–ITEC, Universidade Federal do Pará (UFPA), Belém, PA, Brasil. (renatosm@gmail.com; limao@ufpa.br).
2 Laboratório de Computação Natural (LCN), Centro Universitário do Pará (CESUPA), Belém, PA, Brasil; Movimento Evolucionário e Cooperativo para a Construção do Artificial (MEC2A), Belém, PA, Brasil; PPGEE–ITEC, Universidade Federal do Pará (UFPa), Belém, PA, Brasil. (onoura@gmail.com).
Manuscript received May 7, 2010.
Manuscript accepted for publication August 29, 2010.
]]> Abstract
This paper describes the development of a new hybrid meta–heuristic of optimization based on a viral lifecycle, specifically the retroviruses (the nature's swiftest evolvers), called Retroviral Iterative Genetic Algorithm (RIGA). This algorithm uses Genetics Algorithms (GA) structures with features of retroviral replication, providing a great genetic diversity, confirmed by better results achieved by RIGA comparing with GA applied to some Real–Valued Benchmarking Functions.
Key words: Evolutionary computation, genetic algorithm, viruses, retroviruses, hybrid metaheuristic.
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