Comparison of multi‐objective optimisation approaches for inverse magnetostatic problems

Abstract

Purpose

The aim of the paper is to compare two different approaches to multi‐objective optimisation in magnetostatics; in this way, the case study is investigated as a possible benchmark.

Design/methodology/approach

A Tabu search method modified with ε‐constraint algorithm is compared with a multi‐objective multi‐individual evolution strategy. The case study is the automated shape design of a magnetic pole. In order to reduce the computational cost of solving the direct problem, which requires repeated analyses of the magnetic field, a neural network has been used to approximate the objective functions that depend on the design variables.

Findings

An approximation of the Pareto front for each method is obtained. A twofold comparison between the two methods is made, based on both the result accuracy and the computational cost.

Originality/value

Two different methods were already tested on a case study proposed as a benchmark for multi‐objective optimization in magnetostatics. The paper represents a contribution to bridge the gap between analytical and numerical benchmarks in electromagnetism.

Citation

Carcangiu, S., Di Barba, P., Fanni, A., Mognaschi, M.E. and Montisci, A. (2007), "Comparison of multi‐objective optimisation approaches for inverse magnetostatic problems", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 26 No. 2, pp. 293-305. https://doi.org/10.1108/03321640710727656