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A Comparative Evaluation of Two Global Search Algorithms

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2 Author(s)
Bekey, George A. ; Department of Electrical Engineering-Systems, University of Southern California, University Park, Los Angeles, Calif. 90007. ; Ung, Man T.

Two heuristic methods for locating the global optimum of a multimodal performance index surface are described. One method is based on a modified random creep procedure which first locates a local minimum and then searches the parameter space with vector steps whose mean length gradually increases. The second is a modification of the Kiefer-Wolfowitz stochastic approximation procedure, in which a random perturbation is added to each measurement. Both algorithms are compared by applying them to finding the roots of a nonlinear algebraic equation and to a constrained dynamic optimization problem.

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Systems, Man and Cybernetics, IEEE Transactions on  (Volume:SMC-4 ,  Issue: 1 )