Global convergence for Newton methods in mathematical programming

In constrained optimization problems in mathematical programming, one wants to minimize a functionalf(x) over a given setC. If, at an approximate solutionx _n , one replacesf(x) by its Taylor series expansion through quadratic terms atx _n and denotes byx _n+1 the minimizing point for this overC, one has a direct analogue of Newton's method. The local convergence of this has been previously analyzed; here, we give global convergence results for this and the similar algorithm in which the constraint setC is also linearized at each step.This research was supported in part by the Office of Naval Research, Contract No. N00014-67-0126-0015, and was presented by invitation at the Fifth Gatlinburg Symposium on Numerical Algebra, Los Alamos, New Mexico, 1972.