A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization | Zendy

Wei Wang | Zendy; Shaoli Hua | Zendy; Junjie Tang | Zendy

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A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization

Author(s) -

Wei Wang,

Shaoli Hua,

Junjie Tang

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/854890

Subject(s) - mathematics , proximal gradient methods , convergence (economics) , computation , filter (signal processing) , mathematical optimization , projection (relational algebra) , penalty method , algorithm , gradient method , constrained optimization , matrix (chemical analysis) , function (biology) , computer science , convex function , materials science , geometry , regular polygon , evolutionary biology , economics , composite material , computer vision , biology , economic growth

A generalized gradient projection filter algorithm for inequality constrained optimization is presented. It has three merits. The first is that the amount of computation is lower, since the gradient matrix only needs to be computed one time at each iterate. The second is that the paper uses the filter technique instead of any penalty function for constrained programming. The third is that the algorithm is of global convergence and locally superlinear convergence under some mild conditions

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