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Numerical Comparisons of Path-Following Strategies for a Primal-Dual Interior-Point Method for Nonlinear Programming

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Listed:
  • M. Argáez

    (University of Texas at El Paso)

  • R. Tapia

    (Rice University)

  • L. Velázquez

    (University of Texas at El Paso)

Abstract

An important research activity in primal-dual interior-point methods for general nonlinear programming is to determine effective path-following strategies and their implementations. The objective of this work is to present numerical comparisons of several path-following strategies for the local interior-point Newton method given by El-Bakry, Tapia, Tsuchiya, and Zhang. We conduct numerical experimentation of nine strategies using two central regions, three notions of proximity measures, and three merit functions to obtain an optimal solution. Six of these strategies are implemented for the first time. The numerical results show that the best path-following strategy is that given by Argáez and Tapia.

Suggested Citation

  • M. Argáez & R. Tapia & L. Velázquez, 2002. "Numerical Comparisons of Path-Following Strategies for a Primal-Dual Interior-Point Method for Nonlinear Programming," Journal of Optimization Theory and Applications, Springer, vol. 114(2), pages 255-272, August.
    • Handle: RePEc:spr:joptap:v:114:y:2002:i:2:d:10.1023_a:1016047200413
    DOI: 10.1023/A:1016047200413
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    References listed on IDEAS

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    1. M. Argáez & R. A. Tapia, 2002. "On the Global Convergence of a Modified Augmented Lagrangian Linesearch Interior-Point Newton Method for Nonlinear Programming," Journal of Optimization Theory and Applications, Springer, vol. 114(1), pages 1-25, July.
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