Affiliations: [a] Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy | [b] Department of Industrial Engineering, University of Padova, Padova, Italy
Correspondence:
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Corresponding author: Elisabetta Sieni, Department of Industrial Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy. Tel.: +39 049 8277514; Fax: +39 049 8277599; E-mail:[email protected]
Abstract: The paper proposes a new strategy to improve the
performance of a standard non-dominated sorting algorithm (NSGA) in
approximating the Pareto-optimal solutions of a multi-objective problem by
introducing new individuals in the population miming the effect of
migrations. The design optimization of a power inductor, synthesizing a
uniform magnetic field for magneto-fluid hyperthermia applications, is
considered as a case study to assess the performance of the
migration-modified NSGA algorithm.
