Abstract
In this paper, a novel global search algorithm interstellar search method (ISM) and its hybridization with mesh adaptive direct search (MADS) are proposed. The ISM is a population-based algorithm that is suitable for multimodal function, due to its capability of finding points on the diverse basins of attraction in a short time. The hybridization with MADS supports the fast convergence on adjacent optima from the points that are discovered in global search using ISM. The effectiveness of ISM was validated through test functions, compared with genetic algorithm and particle swarm optimization. Last, the ISM was applied to the optimal design of brushless dc motor aimed for minimizing torque ripples, identified through finite-element analysis.
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