LIMITING DISTRIBUTION FOR RANDOM OPTIMIZATION METHODS

Let f be a function defined on some domain OMEGA contained in R**d. We consider the problem of finding the global minimum of f subjected to some constraints, say g//i(x) less than equivalent to 0, i equals 1,. . . , m. When differentiability is not assumed random optimization methods provide an alternative way to estimate the minimum. For two such methods we study the existence of the limiting distribution and the estimation of the parameter of the limiting distribution.