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Filter Methods

In: Modern Numerical Nonlinear Optimization

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  • Neculai Andrei

    (Center for Advanced Modeling and Optimization)

Abstract

This chapter focuses on the filter methods developed by Fletcher and Leyffer (2002) as a new technique for the globalization of nonlinear optimization algorithms. These methods are motivated by the aim of avoiding the need to choose penalty parameters in penalty functions or in augmented Lagrangian functions and their variants. Let us consider the nonlinear optimization problems with inequality constraints.

Suggested Citation

  • Neculai Andrei, 2022. "Filter Methods," Springer Optimization and Its Applications, in: Modern Numerical Nonlinear Optimization, chapter 18, pages 647-659, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-08720-2_18
    DOI: 10.1007/978-3-031-08720-2_18
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