Tolerance and multiobjective optimization in electromagnetic devices
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Subhasis Ray [1] ; David Lowther [1]
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[1] McGill University
McGill University
Canadá
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- Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 28, Nº 4 (Special Issue: Selected papers from 13th IGTE Symposium), 2009, págs. 1020-1032
- Idioma: inglés
- Enlaces
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Resumen
Purpose – The purpose of this paper is to develop a novel multi‐objective optimization algorithm which takes into account the uncertainty in design parameters by using a reduced resolution for their representation, thus implementing a simple form of robustness. Additionally, the number of function evaluations should be minimized.
Design/methodology/approach – The proposed approach is based on an elitist evolutionary algorithm coupled with a reduction in the number of significant figures used to represent design parameters. In effect, this becomes a filter in the optimization process and allows the system to avoid extremely sharp optima within the search space. By reducing the resolution of the search and maintaining a full archive of previous solutions, the number of evaluations of the objective functions, each of which may require an expensive numerical solution, is reduced.
Findings – The algorithm was tested both on an algebraic test function and on two TEAM Workshop Problems (22 and 25). The results demonstrated that it is stable; can emerge from deceptive fronts; and find optimal solutions which match those previously published at a relatively low‐computational cost.
Originality/value – The originality of this paper lies in the concept of using a low‐resolution representation of the design parameters. This results in a finite size search space and increases the speed of the algorithm while avoiding non‐manufacturable solutions.
