Foundations of Mathematical Optimization

Foundations of Mathematical Optimization PDF

Author: Diethard Ernst Pallaschke

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 597

ISBN-13: 9401715882

DOWNLOAD EBOOK →

Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization. Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.

Foundations of Optimization

Foundations of Optimization PDF

Author: Osman Güler

Publisher: Springer Science & Business Media

Published: 2010-08-03

Total Pages: 445

ISBN-13: 0387684077

DOWNLOAD EBOOK →

This book covers the fundamental principles of optimization in finite dimensions. It develops the necessary material in multivariable calculus both with coordinates and coordinate-free, so recent developments such as semidefinite programming can be dealt with.

Practical Mathematical Optimization

Practical Mathematical Optimization PDF

Author: Jan Snyman

Publisher: Springer Science & Business Media

Published: 2005-12-15

Total Pages: 271

ISBN-13: 0387243496

DOWNLOAD EBOOK →

This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form. It enables professionals to apply optimization theory to engineering, physics, chemistry, or business economics.

Mathematical Theory of Optimization

Mathematical Theory of Optimization PDF

Author: Ding-Zhu Du

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 277

ISBN-13: 1475757956

DOWNLOAD EBOOK →

This book provides an introduction to the mathematical theory of optimization. It emphasizes the convergence theory of nonlinear optimization algorithms and applications of nonlinear optimization to combinatorial optimization. Mathematical Theory of Optimization includes recent developments in global convergence, the Powell conjecture, semidefinite programming, and relaxation techniques for designs of approximation solutions of combinatorial optimization problems.

Foundations of Optimization

Foundations of Optimization PDF

Author: M. S. Bazaraa

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 203

ISBN-13: 3642482945

DOWNLOAD EBOOK →

Current1y there is a vast amount of literature on nonlinear programming in finite dimensions. The pub1ications deal with convex analysis and severa1 aspects of optimization. On the conditions of optima1ity they deal mainly with generali- tions of known results to more general problems and also with less restrictive assumptions. There are also more general results dealing with duality. There are yet other important publications dealing with algorithmic deve10pment and their applications. This book is intended for researchers in nonlinear programming, and deals mainly with convex analysis, optimality conditions and duality in nonlinear programming. It consolidates the classic results in this area and some of the recent results. The book has been divided into two parts. The first part gives a very comp- hensive background material. Assuming a background of matrix algebra and a senior level course in Analysis, the first part on convex analysis is self-contained, and develops some important results needed for subsequent chapters. The second part deals with optimality conditions and duality. The results are developed using extensively the properties of cones discussed in the first part. This has faci- tated derivations of optimality conditions for equality and inequality constrained problems. Further, minimum-principle type conditions are derived under less restrictive assumptions. We also discuss constraint qualifications and treat some of the more general duality theory in nonlinear programming.

Mathematical Foundations of Nature-Inspired Algorithms

Mathematical Foundations of Nature-Inspired Algorithms PDF

Author: Xin-She Yang

Publisher: Springer

Published: 2019-05-08

Total Pages: 107

ISBN-13: 3030169367

DOWNLOAD EBOOK →

This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.

Mathematical Foundations for Signal Processing, Communications, and Networking

Mathematical Foundations for Signal Processing, Communications, and Networking PDF

Author: Erchin Serpedin

Publisher: CRC Press

Published: 2017-12-04

Total Pages: 852

ISBN-13: 1439855145

DOWNLOAD EBOOK →

Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key techniques and comprehend the current research literature, the book offers a comprehensive overview of methods and applications from linear algebra, numerical analysis, statistics, probability, stochastic processes, and optimization. From basic transforms to Monte Carlo simulation to linear programming, the text covers a broad range of mathematical techniques essential to understanding the concepts and results in signal processing, telecommunications, and networking. Along with discussing mathematical theory, each self-contained chapter presents examples that illustrate the use of various mathematical concepts to solve different applications. Each chapter also includes a set of homework exercises and readings for additional study. This text helps readers understand fundamental and advanced results as well as recent research trends in the interrelated fields of signal processing, telecommunications, and networking. It provides all the necessary mathematical background to prepare students for more advanced courses and train specialists working in these areas.

Lanterna Rally - Theme by Grace Themes