Learn More
This paper studies the properties of a class of nonlinear Lagrangians for nonlinear programming with inequality constraints. It's shown that under a set of conditions this class of Lagrange algorithm is locally convergent when the penalty parameter is larger than a threshold. An error bound estimate of the solution, depending on the penalty, is also(More)
  • 1