@InCollection{SambattiCampChiw:2019:PaAl,
author = "Sambatti, Sabrina B. M. and Campos Velho, Haroldo Fraga de and
Chiwiacowski, Leonardo D.",
title = "Epidemic Genetic Algorithm for solving inverse problems: parallel
algorithms",
booktitle = "Integral methods in science and engineering",
publisher = "Springer",
year = "2019",
editor = "Constanda, Christian and Harris, Paul",
pages = "381--394",
address = "Brighton, UK",
keywords = "Genetic algorithm, parallel computing, inverse problem.",
abstract = "Parallel Genetic Algorithm (PGA) is employed to solve inverse
problems. The PGA is codified considering the island model
(individuals are free to migrate to any other processor, subjected
to specific rules); and steppingstone model (migration is allowed
only for closest processors). The parallel code is generated using
calls to the message passing communication library MPI (Message
Passing Interface). In the our GA approach, a new genetic
operator, named epidemic, is applied. The technique is employed to
solve an inverse heat conduction problem of determining the
initial temperature from the transient noisy temperature profile
at a given time. This ill-posed problem requires the use of a
regularization technique.",
affiliation = "{Clima Tempo} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {University of Caxias}",
isbn = "978-3-030-16077-7",
language = "en",
targetfile = "sambatti-epidemic.pdf",
urlaccessdate = "27 abr. 2024"
}