Nonlinear Programming

Author: Peter Zörnig
Publisher: Walter de Gruyter
ISBN: 3110315289
Size: 51.92 MB
Format: PDF, Mobi
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Nonlinear Programming from the Author: Peter Zörnig. This book is an introduction to nonlinear programming, written for students from the fields of applied mathematics, engineering, and economy. It deals with theoretical foundations as well as solution methods, beginning with the classical procedures and reaching up to “modern” methods. Several examples, exercises with detailed solutions and applications are provided, making the text adequate for individual studies.

Introduction To Optimization

Author: Pablo Pedregal
Publisher: Springer Science & Business Media
ISBN: 0387403981
Size: 45.77 MB
Format: PDF, Mobi
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Introduction To Optimization from the Author: Pablo Pedregal. This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.

An Introduction To Nonlinear Optimization Theory

Author: Marius Durea
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110426048
Size: 75.81 MB
Format: PDF, Kindle
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An Introduction To Nonlinear Optimization Theory from the Author: Marius Durea. This book presents the main ideas and techniques in the field of continuous smooth and nonsmooth optimization.

Nonlinear Programming

Author: Lorenz T. Biegler
Publisher: SIAM
ISBN: 0898719380
Size: 13.42 MB
Format: PDF, Mobi
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Nonlinear Programming from the Author: Lorenz T. Biegler. This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.

Methods Of Mathematical Economics

Author: Joel N. Franklin
Publisher: SIAM
ISBN: 9780898719239
Size: 48.51 MB
Format: PDF, Kindle
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Methods Of Mathematical Economics from the Author: Joel N. Franklin. Linear programming. Introduction to linear programming -- Linear programs and their duals -- How the dual indicates optimality -- Basic solutions -- The idea of the simplex methods -- Separating planes for convex sets -- Finite cones and the Farkas alternative -- The duality principle -- Perturbations and parametric programming -- The simplex tableau algorithm -- The revised simplex algorithm -- A simplex algorithm for degenerate problems -- Multiobjective linear programming -- Zero-sum, two-person games -- Integer programming: Gomory's method -- Network flows -- Assignment and shortest-route problems -- The transportation problem -- Nonlinear programming. Wolfe's method for quadratic programming -- Kuhn-Tucker theory -- Geometric programming -- Fixed-point theorems. Introduction to fixed points -- Contraction mappings -- Garsia's proof of the Brouwer fixed-point theorem -- Milnor's proof of the Brouwer fixed-point theorem -- Barycentric coordinates, Sperner's lemma, and an elementary proof of the Brouwer fixed-point theorem -- The Schauder fixed-point theorem -- Kakutani's fixed-point theorem and Nash's theorem for n-person games.

Nonlinear Programming For Operations Research

Author: Donald M. Simmons
Publisher: Prentice Hall
ISBN:
Size: 68.43 MB
Format: PDF, Kindle
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Nonlinear Programming For Operations Research from the Author: Donald M. Simmons. Introduction to nonlinear programming; Review of linear programming; Further mathematical background; Classical uncostrained optimization; Optimum-seeking by experimentation; Lagrange multipliers and kuhn-tucker theory; Quadratic programming; Algorithms for linearly constrained problems; Algorithms for nonlinear constrained problems.