Migration NSGA: method to improve a non-elitist searching of Pareto front, with application in magnetics

DOI10.1080/17415977.2015.1047366zbMath1342.78009OpenAlexW2228711021MaRDI QIDQ3177931

Paolo Di Barba, M. Forzan, E. Sieni

Publication date: 8 July 2016

Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17415977.2015.1047366

zbMATH Keywords

multi-objective optimizationPareto frontanalytical problemmagnetic case studynon-dominated sorted algorithm

Mathematics Subject Classification ID

Electromagnetic theory (general) (78A25) Software, source code, etc. for problems pertaining to optics and electromagnetic theory (78-04)

Related Items (1)

Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Cites Work

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• A self-organizing migrating genetic algorithm for constrained optimization
• Global optimization of thermal conductivity using stochastic algorithms
• Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design
• Theory of genetic algorithms

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