Titlebook: Linear and Nonlinear Programming; David G. Luenberger,Yinyu Ye Textbook 2021Latest edition Springer Nature Switzerland AG 2021 Linear Prog

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Basic Properties of Solutions and Algorithmst, is a subset of ... Throughout most of the chapter attention is restricted to the case where Ω?=?.., corresponding to the completely unconstrained case, but sometimes we consider cases where Ω is some particularly simple subset of ...

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Conjugate Direction Methodsted by the desire to accelerate the typically slow convergence associated with steepest descent while avoiding the information requirements associated with the evaluation, storage, and inversion of the Hessian (or at least solution of a corresponding system of equations) as required by Newton’s method.

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Local Duality and Dual Methodsf the local dual are again the Lagrange multipliers associated with the constraints in the primal problem—the original constrained optimization problem but restricted in the neighborhood of a primal solution under consideration.

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Primal–Dual Methodsions for optimality. The methods employ many of the concepts used in earlier chapters, including those related to active set methods, various first- and second-order methods, penalty methods, and barrier methods. Indeed, a study of this chapter is in a sense a review and extension of what has been presented earlier.

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David G. Luenberger,Yinyu YeUpdated to include new research findings such as Machine Learning Optimization.Provides a structure for learning existing material and insights for developing new results.Features end-of-chapter exerc

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978-3-030-85452-2Springer Nature Switzerland AG 2021

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Linear and Nonlinear Programming978-3-030-85450-8Series ISSN 0884-8289 Series E-ISSN 2214-7934