Title: Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix Classic Reprint
Publisher: Forgotten Books
Publication Date: 2018
Language: English
ISBN 10: 0656569611
ISBN 13: 9780656569618
Binding: HRD
Condition: New
Weight: 423 grams

About this title

Synopsis

Discover how projected Hessian updates drive efficient, reliable optimization in constrained problems.

This book explains sequential quadratic programming (SQP) methods that use an approximation to second-derivative information projected onto the constraint tangent space. It focuses on maintaining a positive definite representation in the reduced space, which helps stabilize updates and enable standard quasi-Newton techniques. The text covers how active and working sets are identified and how the projected Hessian guides subproblem formulations and iterations.

How the projected Hessian enters optimality conditions and how to form and update it in practice
Ways to manage the working set, including dropping criteria and their impact on convergence
Update rules and safeguards that keep the projected Hessian well-behaved and numerically stable
Convergence results for a restricted class of problems and practical insights from numerical results

Ideal for readers who want a rigorous, implementation-conscious view of SQP methods and the role of projected Hessian information in constrained optimization.

"About this title" may belong to another edition of this title.

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