This analysis compares deterministic and stochastic global optimization strategies, revealing that stochastic methods outperform deterministic ones in electromechanical applications.
Global optimization methodologies, belonging to both the deterministic and the stochastic class, are discussed. A higher-order-deterministic optimizer and a zeroth-order-stochastic one are compared for the solution of a practical case study, taken from electromechanics. A non-linear constrained design problem is formulated and solutions, in terms of optimal shapes of the device considered, are determined. Some improvements in generating feasible random configurations have been suggested. On average, stochastic zeroth-order strategies were superior to their deterministic higher-order counterparts.
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Barba et al. (1993) studied this question.
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