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Improved solutions to a TEAM problem for multi-objective optimisation in magnetics

Improved solutions to a TEAM problem for multi-objective optimisation in magnetics
Improved solutions to a TEAM problem for multi-objective optimisation in magnetics
New solutions to a recently proposed benchmark TEAM problem for Pareto optimisation are presented. In the benchmark, an air-cored solenoid of small size, which can be used, for example, for magnetic fluid hyperthermia, is considered. Two shape optimisations of the solenoid are proposed in the benchmark: synthesising a uniform magnetic field in a control region, considering also a sensitivity function (Problem 1) or synthesising a uniform magnetic field, simultaneously minimising the power losses (Problem 2). The benchmark is solved by means of three different nature-inspired algorithms and a genetic one, namely micro biogeography-inspired algorithm, wind-driven optimisation, and the cuckoo search, taking the genetic algorithm NSGA-II as a reference, because all these methods have proven to be effective in solving multi-objective optimisation problems.
Pareto optimisation, TEAM problem, air-cored solenoid, biomagnetism, control region, different nature-inspired algorithms, evolutionary computation, genetic algorithm NSGA-II, genetic algorithms, hyperthermia, magnetic fluid hyperthermia, magnetic fluids, magnetics, microbiogeography-inspired, minimisation, multiobjective optimisation problems, optimisation, search problems, sensitivity function, shape optimisations, solenoids, uniform magnetic field, wind-driven optimisation
1751-8822
964-968
Di Barba, Paolo
2a71a034-4c2a-4e74-9e8f-9ccd7fa88104
Mognaschi, Maria Evelina
83f56dbc-0ab4-400c-93fd-c51d7827b217
Lowther, David A.
0cf19bca-4eac-4b03-a916-fe9b5df0dfc0
Sykulski, Jan K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Di Barba, Paolo
2a71a034-4c2a-4e74-9e8f-9ccd7fa88104
Mognaschi, Maria Evelina
83f56dbc-0ab4-400c-93fd-c51d7827b217
Lowther, David A.
0cf19bca-4eac-4b03-a916-fe9b5df0dfc0
Sykulski, Jan K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Di Barba, Paolo, Mognaschi, Maria Evelina, Lowther, David A. and Sykulski, Jan K. (2020) Improved solutions to a TEAM problem for multi-objective optimisation in magnetics. IET Science, Measurement & Technology, 14 (8), 964-968. (doi:10.1049/iet-smt.2019.0488).

Record type: Article

Abstract

New solutions to a recently proposed benchmark TEAM problem for Pareto optimisation are presented. In the benchmark, an air-cored solenoid of small size, which can be used, for example, for magnetic fluid hyperthermia, is considered. Two shape optimisations of the solenoid are proposed in the benchmark: synthesising a uniform magnetic field in a control region, considering also a sensitivity function (Problem 1) or synthesising a uniform magnetic field, simultaneously minimising the power losses (Problem 2). The benchmark is solved by means of three different nature-inspired algorithms and a genetic one, namely micro biogeography-inspired algorithm, wind-driven optimisation, and the cuckoo search, taking the genetic algorithm NSGA-II as a reference, because all these methods have proven to be effective in solving multi-objective optimisation problems.

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e-pub ahead of print date: 24 September 2020
Keywords: Pareto optimisation, TEAM problem, air-cored solenoid, biomagnetism, control region, different nature-inspired algorithms, evolutionary computation, genetic algorithm NSGA-II, genetic algorithms, hyperthermia, magnetic fluid hyperthermia, magnetic fluids, magnetics, microbiogeography-inspired, minimisation, multiobjective optimisation problems, optimisation, search problems, sensitivity function, shape optimisations, solenoids, uniform magnetic field, wind-driven optimisation

Identifiers

Local EPrints ID: 445334
URI: http://eprints.soton.ac.uk/id/eprint/445334
ISSN: 1751-8822
PURE UUID: 1ee18186-ab88-4ef9-af50-d0de3b0ff4e3
ORCID for Jan K. Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

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Date deposited: 02 Dec 2020 17:32
Last modified: 02 Dec 2020 17:32

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Contributors

Author: Paolo Di Barba
Author: Maria Evelina Mognaschi
Author: David A. Lowther
Author: Jan K. Sykulski ORCID iD

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