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2. Mixing Theory of Retroviruses and Genetic Algorithm to Build a New Nature-Inspired Meta-Heuristic for Real-Parameter Function Optimization Problems

Author

Roberto Célio Limão de Oliveira, Otávio Noura Teixeira, and Renato Simões Moreira

Subjects
Mathematical optimization, Theoretical computer science, Iterative method, Computer science, Genetic algorithm, Meta heuristic, Benchmarking, Nature inspired, Function optimization problems, Evolutionary computation, Replication (computing)
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.

Published
2010
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