Springer series in operations research and financial engineering
Includes bibliographical references (pages 637-652) and index.
Fundamentals of Unconstrained Optimization -- Line Search Methods -- Trust-Region Methods -- Conjugate Gradient Methods -- Quasi-Newton Methods -- Large-Scale Unconstrained Optimization -- Calculating Derivatives -- Derivative-Free Optimization -- Least-Squares Problems -- Nonlinear Equations -- Theory of Constrained Optimization -- Linear Programming: The Simplex Method -- Linear Programming: Interior-Point Methods -- Fundamentals of Algorithms for Nonlinear Constrained Optimization -- Quadratic Programming -- Penalty and Augmented Lagrangian Methods -- Sequential Quadratic Programming -- Interior-Point Methods for Nonlinear Programming.
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'Numerical Optimization' presents a comprehensive description of the effective methods in continuous optimization. The book includes chapters on nonlinear interior methods & derivative-free methods for optimization. It is useful for graduate students, researchers and practitioners.
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.