%0 Journal Article
%4 sid.inpe.br/mtc-m21c/2018/03.07.18.57
%2 sid.inpe.br/mtc-m21c/2018/03.07.18.57.54
%@issn 2359-0793
%T Multi-Particle collision algorithm with Hooke Jeeves applied to the damage identification in a Kabe problem
%D 2018
%9 conference paper
%A Hernández Torres, Reynier,
%A Campos Velho, Haroldo Fraga de,
%A Chiwiacowsky, Leonardo D.,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de Caxias do Sul (UCS)
%@electronicmailaddress reynier.torres@inpe.br
%@electronicmailaddress haroldo@lac.inpe.br
%@electronicmailaddress ldchiwiacowsky@ucs.br
%B Proceeding Series of the Brazilian Society of Applied and Computational Mathematics
%V 6
%N 1
%P 010399
%K Hybrid metaheuristic, rotation-based learning, opposition-based learning, multiparticle collision algorithm.
%X A new variant of the hybrid metaheutic MPCAHJ (Multi-Particle Collision Algorithm with Hooke-Jeeves method) is presented. Multi-Particle Collision Algorithm is a metaheuristic algorithm that performs a search on the search space. With the addition of the Rotation-Based Learning mechanism to the exploration search, a maior area of the search space has chance to be visited. The Hooke-Jeeves direct search method exploites the best solution found, allowing to achieve better solutions. The performance of all implementation are evaluated over twenty-two well known benchmark functions.
%@language en
%3 Torres_multi-particle.pdf
%O Trabalho apresentado no XXXVII CNMAC, S.J. dos Campos - SP, 2017.