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Convergence to Second-Order Stationary Points of a Primal-Dual Algorithm Model for Nonlinear Programming

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  • Gianni Di Pillo

    () (Dipartimento di Informatica e Sistemistica “Antonio Ruberti,” Università di Roma “La Sapienza,” via Buonarroti 12, 00185 Roma, Italy)

  • Stefano Lucidi

    () (Dipartimento di Informatica e Sistemistica “Antonio Ruberti,” Università di Roma “La Sapienza,” via Buonarroti 12, 00185 Roma, Italy)

  • Laura Palagi

    () (Dipartimento di Informatica e Sistemistica “Antonio Ruberti,” Università di Roma “La Sapienza,” via Buonarroti 12, 00185 Roma, Italy)

Abstract

We define a primal-dual algorithm model (second-order Lagrangian algorithm, SOLA) for inequality constrained optimization problems that generates a sequence converging to points satisfying the second-order necessary conditions for optimality. This property can be enforced by combining the equivalence between the original constrained problem and the unconstrained minimization of an exact augmented Lagrangian function and the use of a curvilinear line search technique that exploits information on the nonconvexity of the augmented Lagrangian function.

Suggested Citation

  • Gianni Di Pillo & Stefano Lucidi & Laura Palagi, 2005. "Convergence to Second-Order Stationary Points of a Primal-Dual Algorithm Model for Nonlinear Programming," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 897-915, November.
  • Handle: RePEc:inm:ormoor:v:30:y:2005:i:4:p:897-915
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    File URL: http://dx.doi.org/10.1287/moor.1050.0150
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    References listed on IDEAS

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