Purpose – The purpose of this paper is to show that the performance of differential evolution (DE) can be substantially improved by a combination of techniques. These enhancements are applicable to both single and multiobjective problems. Their combined use allows the optimization of complex 3D electromagnetic devices. Design/methodology/approach – DE is improved by a combination of techniques which are applied in a cascade way and their single and combined effect is tested on well‐known benchmarks and domain‐specific applications. Findings – It is shown that the combined use of enhancement techniques provides substantial improvements in the speed of convergence for both single and multiobjective problems. Research limitations/implications – The increased speed of convergence may come at the price of a somewhat decreased robustness. However, such behavior is justified by the CPU time constraints under which the optimization has to be performed. Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems. Originality/value – This paper explorers the combined use of many of the most recent and successful algorithmic improvements to DE and applies them to both single and multiobjective problems.
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing
Published: Nov 15, 2011
Keywords: Stochastic optimization; Multiobjective optimization; Differential evolution; Parallel computing; Electromagenetism; Computer hardware
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