Algoritms of nonlinear programming which approximate the achievability function

The possibility of designing algorithms for numerical solution of nonlinear programming problems is considered whereby the relation between the achievability function of the initial problem and of an unconditional optimization problem with a modified goal function is used. The algorithms proceed by succes-size approximation of the achievability function of the initial problem and a choice of goal function parameters in the problem of unconditional optimization such that the maximum of the function is on the set of feasible solutions of the initial problem.