Recursive quadratic programming methods based on the augmented lagrangian

This publication has 12 references indexed in Scilit:

• A recursive quadratic programming algorithm that uses differentiable exact penalty functions
  Mathematical Programming, 1986
• The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function
  Numerische Mathematik, 1982
• The watchdog technique for forcing convergence in algorithms for constrained optimization
  1982
• Computation of the search direction in constrained optimization algorithms
  1982
• Test Examples for Nonlinear Programming Codes
  1981
• A fast algorithm for nonlinearly constrained optimization calculations
  1978
• On the Convergence of Some Constrained Minimization Algorithms Based on Recursive Quadratic Programming
  IMA Journal of Applied Mathematics, 1978
• A globally convergent method for nonlinear programming
  Journal of Optimization Theory and Applications, 1977
• AN IDEAL PENALTY FUNCTION FOR CONSTRAINED OPTIMIZATION11This paper has been published in the Journal of the Institute of Mathematics and Its Applications. It is being published here at the invitation of the editors and with the permission of the Institute of Mathematics and Its Applications. There are some small differences which are explained in the ‘Note in Proof.’
  1975
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
  IMA Journal of Applied Mathematics, 1970