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A new numerically efficient global optimization algorithm utilizing grid computing technique and surrogate objective function (SOF) is developed. The algorithm combines particles swarm optimization (PSO) with a SOF constructed by using Multi-quadric radial basis function. For the computation of the objective function values for sampling points, grid computing technique is adopted employing the same...
A permanent magnet linear synchronous motor (PMLSM) is shape optimized in Pareto sense to get a minimum detent force and maximum thrust force per mass. In the optimization, a surrogate objective function is constructed with the help of grid computing technique by using Multi-quadric radial basis function to reduce the computing time related with finite element analysis.
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