In the paper the optimal synthesis of the magnetic field in a device for Magneto-Fluid Hyperthermia (MFH) tests on cell cultured in Petri dishes is presented. Magneto-Fluid Hyperthermia is a cancer therapy that exploits magnetic fluid and time-harmonic magnetic field to heat nanoparticles localized in the target region. To this end, a modified version of Non-Dominated Sorting Genetic Algorithm (NSGA-II) is presented. The proposed optimization algorithm includes the periodic migration of a new population that enhances the genetic heritage of the current population. The convergence of the algorithm is automatically controlled by applying a suitable 'stop criterion'. The optimal design of a class of power inductors for MFH is considered.

SELF-adaptive Migration-NSGA algorithm: An application in uncertainty-tolerant magnetic field synthesis for MFH inductor design

Forzan, Michele;Sieni, Elisabetta
2018

Abstract

In the paper the optimal synthesis of the magnetic field in a device for Magneto-Fluid Hyperthermia (MFH) tests on cell cultured in Petri dishes is presented. Magneto-Fluid Hyperthermia is a cancer therapy that exploits magnetic fluid and time-harmonic magnetic field to heat nanoparticles localized in the target region. To this end, a modified version of Non-Dominated Sorting Genetic Algorithm (NSGA-II) is presented. The proposed optimization algorithm includes the periodic migration of a new population that enhances the genetic heritage of the current population. The convergence of the algorithm is automatically controlled by applying a suitable 'stop criterion'. The optimal design of a class of power inductors for MFH is considered.
Multiobjective optimization; genetic algorithm; Pareto optimality; magnetic field; finite-element analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11383/2077321
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