Migration-corrected NSGA-II for improving multiobjective design optimization in electromagnetics
Articolo
Data di Pubblicazione:
2016
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.
Tipologia CRIS:
Articolo su Rivista
Keywords:
finite-element analysis; genetic algorithm; magnetic field; Multiobjective optimization; Pareto optimality; Electrical and Electronic Engineering; Mechanical Engineering; Mechanics of Materials; Condensed Matter Physics; Electronic; Optical and Magnetic Materials
Elenco autori:
Di Barba, Paolo; Dughiero, Fabrizio; Forzan, Michele; Sieni, Elisabetta
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