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

被引:5
作者
Di Barba, Paolo [1 ]
Mognaschi, Maria Evelina [1 ]
Lowther, David A. [2 ]
Sykulski, Jan K. [3 ]
机构
[1] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy
[2] McGill Univ, Dept Comp & Elect Engn, Montreal, PQ, Canada
[3] Univ Southampton, Elect & Comp Sci, Southampton, Hants, England
关键词
genetic algorithms; hyperthermia; search problems; Pareto optimisation; magnetic fluids; evolutionary computation; solenoids; optimisation; minimisation; biomagnetism; TEAM problem; magnetics; air-cored solenoid; magnetic fluid hyperthermia; shape optimisations; uniform magnetic field; control region; sensitivity function; different nature-inspired algorithms; microbiogeography-inspired; wind-driven optimisation; genetic algorithm NSGA-II; multiobjective optimisation problems; WIND-DRIVEN OPTIMIZATION; BIOGEOGRAPHY; ALGORITHM; NSGA;
D O I
10.1049/iet-smt.2019.0488
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:964 / 968
页数:5
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