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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generalized gradient projection filter algorithm penalty function gradient matrix inequality constrained optimization filter technique

Shaoli Hua,Junjie Tang,.A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization. 2013 (),.

Shaoli Hua,Junjie Tang,"A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization" 2013

Shaoli Hua,Junjie Tang,"A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization"