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2008•Journal of Xinxiang UniversityRequires access

A New Filter SQP Algorithm for Inequality Constrained Optimization

Chungen Shen

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Abstract

The paper introduces a new filter SQP algorithm based on line search technique.This algorithm uses neither a penalty function nor a restoration phase.The global convergence is proved under some mild conditions.We do some improvement of the acceptance conditions of the line search filter so that the trial steps can be accepted easily.Numerical results are presented that confirm the robustness of our algorithm.

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What this paper is about

The paper introduces a new filter SQP algorithm based on line search technique.This algorithm uses neither a penalty function nor a restoration phase.The global convergence is proved under some mild conditions.We do some improvement of the acceptance conditions of the line search filter so that the trial steps can be accepted easily.Numerical results are presented that confirm the robustness of our algorithm.

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Available abstract

The paper introduces a new filter SQP algorithm based on line search technique.This algorithm uses neither a penalty function nor a restoration phase.The global convergence is proved under some mild conditions.We do some improvement of the acceptance conditions of the line search filter so that the trial steps can be accepted easily.Numerical results are presented that confirm the robustness of our algorithm.

Key concepts: Sequential quadratic programming, Robustness (evolution), Mathematical optimization, Penalty method, Line search, Convergence (economics), Filter (signal processing), Algorithm

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