@Article{HernándezTorresCampChiw:2018:MuCoAl,
author = "Hern{\'a}ndez Torres, Reynier and Campos Velho, Haroldo Fraga de
and Chiwiacowsky, Leonardo D.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Universidade de
Caxias do Sul (UCS)}",
title = "Multi-Particle collision algorithm with Hooke Jeeves applied to
the damage identification in a Kabe problem",
journal = "Proceeding Series of the Brazilian Society of Applied and
Computational Mathematics",
year = "2018",
volume = "6",
number = "1",
pages = "010399",
note = "Trabalho apresentado no XXXVII CNMAC, S.J. dos Campos - SP,
2017.",
keywords = "Hybrid metaheuristic, rotation-based learning, opposition-based
learning, multiparticle collision algorithm.",
abstract = "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.",
issn = "2359-0793",
language = "en",
targetfile = "Torres_multi-particle.pdf",
urlaccessdate = "27 abr. 2024"
}