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.
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Moreira, R.S., Monteiro, G.D., Teixeira, O.N., Soares, Á.S., de Oliveira, R.C.L. (2010). Retroviral Iterative Genetic Algorithm for Real Parameter Function Optimization Problems. In: Cai, Z., Hu, C., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2010. Lecture Notes in Computer Science, vol 6382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16493-4_23
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DOI: https://doi.org/10.1007/978-3-642-16493-4_23
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