The Linear Convergence of a Successive Linear
Programming Algorithm
y z
Michael C Ferris Sergei K Zavriev
December
Abstract
We present a successive linear programming algorithm for solving
constrained nonlinear optimization problems The algorithm employs
an Armijo pro cedure for up dating a trust region radius We prove the
linear convergence of the metho d by relating the solutions of our sub
problems to standard trust region and gradient pro jection subproblems
and adapting an error b ound analysis due to Luo and Tseng Com
putational results are provided for p olyhedrally constrained nonlinear
programs