Open AccessMicro biogeography‐inspired multi‐objective optimisation for industrial electromagnetic design
Author(s) -
Mognaschi M.E.
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2017.3072
Subject(s) - electromagnetics , novelty , evolutionary algorithm , function (biology) , computer science , mathematical optimization , field (mathematics) , multi objective optimization , benchmark (surveying) , test functions for optimization , algorithm , artificial intelligence , engineering , mathematics , optimization problem , electronic engineering , philosophy , theology , geodesy , evolutionary biology , pure mathematics , biology , geography , multi swarm optimization
In this Letter, the micro biogeography‐inspired multi‐objective optimisation (μBiMO) method, an extension of the biogeography‐inspired multi‐objective optimisation (BiMO) algorithm, is proposed. It is suitable for solving multi‐objective optimisations in the field of industrial design because it is based on a small number of islands (hence the name μBiMO), i.e. few objective function calls are required. An analytical test function is used for evaluating the performances of the standard BiMO method and to show the need for the proposed μBiMO algorithm. To test its performances in industrial applications, an optimal shape design problem in electromagnetics, i.e. an electromagnet optimal design, has been chosen as a case study. To the best knowledge of the author, the main element of novelty of the Letter is that the BiMO algorithm has been applied for the first time to a multi‐objective design with a reduced number of islands (μBiMO). The algorithm so modified leads to a strong reduction of computational time, and, at the same time, improves the quality of results.