Probabilistic version of the method of feasible directions

摘要

A probabilistic version of the method of feasible directions (MFD) for solving nonlinear programming (NLP) problems of the type min{f(x): fj(x)⩽0,j=1,2,…,m} is presented. Randomization is applied to modify the algorithm and a global convergence Theorem is used in the analysis of convergence. Some numerical experiments on problems with known solutions serve to compare this method with the traditional deterministic versions.