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Self-adaptive migration NSGA and optimal design of inductors for magneto-fluid hyperthermia

Elisabetta Sieni (Department of Industrial Engineering, University of Padova, Padova, Italy)
Paolo Di Barba (Department of Electrical Engineering, University of Pavia, Pavia, Italy)
Fabrizio Dughiero (Department of Industrial Engineering, University of Padova, Padova, Italy)
Michele Forzan (Department of Industrial Engineering, University of Padova, Padova, Italy)

Engineering Computations

ISSN: 0264-4401

Article publication date: 6 July 2018

Issue publication date: 23 July 2018

Abstract

Purpose

The purpose of this paper is to present a modified version of the non-dominated sorted genetic algorithm with an application in the design optimization of a power inductor for magneto-fluid hyperthermia (MFH).

Design/methodology/approach

The proposed evolutionary algorithm is a modified version of migration-non-dominated sorting genetic algorithms (M-NSGA) that now includes the self-adaption of migration events- non-dominated sorting genetic algorithms (SA-M-NSGA). Moreover, a criterion based on the evolution of the approximated Pareto front has been activated for the automatic stop of the computation. Numerical experiments have been based on both an analytical benchmark and a real-life case study; the latter, which deals with the design of a class of power inductors for tests of MFH, is characterized by finite element analysis of the magnetic field.

Findings

The SA-M-NSGA substantially varies the genetic heritage of the population during the optimization process and allows for a faster convergence.

Originality/value

The proposed SA-M-NSGA is able to find a wider Pareto front with a computational effort comparable to a standard NSGA-II implementation.

Keywords

Acknowledgements

The authors would like to thank Mr. Luca Bonin Aselt spa, VI, Italy, for the realization of the inductor.

Citation

Sieni, E., Di Barba, P., Dughiero, F. and Forzan, M. (2018), "Self-adaptive migration NSGA and optimal design of inductors for magneto-fluid hyperthermia", Engineering Computations, Vol. 35 No. 4, pp. 1727-1746. https://doi.org/10.1108/EC-05-2016-0186

Publisher

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Emerald Publishing Limited

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