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An Improvement Feasible Descent Method for SQP and Its Global Convergenle

Liuqing Ye, SI Qing-liang, Shaochun Chen

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Abstract

In this paper,by using generalized projection rectify technique,Mutilated search direction.through improved suppose conditions,by using a new one order correcting direction and combining with the SQP skill,a new SQP feasible descent algorithm for nonlinear constrained optimitation problem(p) is presented,and under weaker conditions,we proofed the new methods still possesses global convergence.the new methods only use little storage,thus the methods are attractine for largeseale problems.

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What this paper is about

In this paper,by using generalized projection rectify technique,Mutilated search direction.through improved suppose conditions,by using a new one order correcting direction and combining with the SQP skill,a new SQP feasible descent algorithm for nonlinear constrained optimitation problem(p) is presented,and under weaker conditions,we proofed the new methods still possesses global convergence.the new methods only use little storage,thus the methods are attractine for largeseale problems.

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Available abstract

In this paper,by using generalized projection rectify technique,Mutilated search direction.through improved suppose conditions,by using a new one order correcting direction and combining with the SQP skill,a new SQP feasible descent algorithm for nonlinear constrained optimitation problem(p) is presented,and under weaker conditions,we proofed the new methods still possesses global convergence.the new methods only use little storage,thus the methods are attractine for largeseale problems.

Key concepts: Sequential quadratic programming, Descent (aeronautics), Mathematical optimization, Convergence (economics), Descent direction, Mathematics, Projection (relational algebra), Computer science

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