stochastic differential equations
Springer Online Journal Archives 1860-2000
Abstract Let ℝ n be then-dimensional real Euclidean space,x=(x 1,x 2, ...,x n)T ∈ ℝ n , and letf:ℝ n → R be a real-valued function. We consider the problem of finding the global minimizers off. A new method to compute numerically the global minimizers by following the paths of a system of stochastic differential equations is proposed. This method is motivated by quantum mechanics. Some numerical experience on a set of test problems is presented. The method compares favorably with other existing methods for global optimization.
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