Generalized extremal optimization: an application in heat pipe design
type: Item
instance of: scholarly article
title: Generalized extremal optimization: an application in heat pipe design
zbMATH Open document ID: 1147.90425
author: Fabiano Luis de Sousa
author: Fernando M. Ramos
author: V. V. Vlassov
published in: Applied Mathematical Modelling
publication date: 2005-05-12T00:00:00Z
review text: A global-optimization algorithm, called ``generalized extremal optimization'', is presented and applied to one specific problem. The algorithm is a global search meta-heuristic, as the genetic or the simulated-annealing algorithms, but adjusting only one free parameter at each step. No information about gradient of the cost functional is needed, of course. The illustration problem, described in detail, concerns a lumped-parameter model of a heat pipe and its optimization involves only 7 scalar variables and 18 constraints. Numerical results of this case study are exposed. No comparison with other optimization algorithms is presented.
reviewed by: Tomáş Roubíçek
Mathematics Subject Classification ID: 90C90
Mathematics Subject Classification ID: 80M50
Mathematics Subject Classification ID: 80A20
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 2167682
zbMATH Keywords: global optimization
zbMATH Keywords: self-organized criticality
zbMATH Keywords: optimal design
zbMATH Keywords: heat pipe
MaRDI profile type: Publication
full work available at URL: j.apm.2004.04.004
OpenAlex ID: W2038551327
cites work: Handbook of global optimization. Vol. 2
cites work: Optimization by Simulated Annealing
cites work: Q4692508
cites work: Q4353479
cites work: Constraint handling in genetic search using expression strategies
cites work: Progressive genetic algorithm for solution of optimization problems with nonlinear equality and inequality constraints
DOI: 10.1016/J.APM.2004.04.004
description: scientific article; zbMATH DE number 2167682