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.
Migration-corrected NSGA-II for improving multiobjective design optimization in electromagnetics
Forzan Michele;Sieni Elisabetta
2016-01-01
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.
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