A REVIEW OF LINE SEARCH SEQUENTIAL QUADRATIC PROGRAMMING AND IT IS RATE OF CONVERGENCE

Abstract

In the last few years the sequential quadratic programming (SQP) methods proposed by Wilson and developed by Han and Powell have widely been  recognized as most effective methods for solving nonlinearly constrained optimization problems which can be classified into two categories trust region and line search methods. In this paper we give a review on line search algorithms for equality constrained optimization and prove that the sequence generated by SQP using a line search under certain conditions has global and local superlinear convergence