2019-05-162019-05-162018CRISPINO, Gabriel Nunes. Paralelização de algoritmo genético com operador não convencional. Orientador: Claudomiro de Souza de Sales Junior. 2018. 56 f. Trabalho de Curso (Bacharelado em Ciência da Computação) – Faculdade de Computação, Instituto de Ciências Exatas e Naturais, Universidade Federal do Pará, Belém, 2018. Disponível em: http://bdm.ufpa.br/jspui/handle/prefix/1341. Acesso em:.http://bdm.ufpa.br/jspui/handle/prefix/1341Parallel genetic algorithms take advantage of concurrent execution to obtain better results and better use of the machine’s hardware. Usually there are multiple subpopulations that evolve concurrently and communicate through a defined migration policy, to achieve better exploration of the search space, for example. Non conventional genetic operators are the ones inspired by some natural organisms, such as viruses and bacteria, to modify the genetic algorithm architechture. It’s common that these operators use auxiliar populations containing special individuals to obtain better genetic variability. This work proposes an implementation of a parallel genetic algorithm that makes use of the recombination by bacterial transformation genetic operator, and then compares its performance with both sequential genetic algorithms that make use of this same operator and parallel versions that use conventional genetic operators. The results show that the presented implementation in general brought a higher speed of convergence, higher robustness, and precision, if compared to the other implementations that are used.Acesso AbertoOperadores genéticos não convencionaisComputação paralelaAlgoritmos genéticosOtimizaçãoAlgoritmos genéticos paralelosCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOTrabalho de Curso - Graduação - Monografia