A line search filter algorithm with inexact step computations for equality constrained optimization

Authors:
Xiaojing Zhu;Dingguo Pu
Affiliations:
Department of Mathematics, Tongji University, Shanghai 200092, China;Department of Mathematics, Tongji University, Shanghai 200092, China
Venue:
Applied Numerical Mathematics
Year:
2012

Citing 14
Cited 0

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An inexact Newton method for nonconvex equality constrained optimization

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A Truncated SQP Method Based on Inexact Interior-Point Solutions of Subproblems

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Abstract

In this paper, a new line search filter algorithm for equality constrained optimization is presented. The approach belongs to the class of inexact Newton-like methods. It can also be regarded as an inexact version of generic sequential quadratic programming (SQP) methods. The trial step is obtained by truncatedly solving the primal-dual system based on any robust and efficient linear system solver. Practical termination tests for the linear system solver are established to ensure global convergence. Preliminary numerical results demonstrate the approach is potentially useful.