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Foundations of Mathematical Optimization

Foundations of Mathematical Optimization PDF Author: Diethard Ernst Pallaschke
Publisher: Springer Science & Business Media
ISBN: 9401715882
Category : Mathematics
Languages : en
Pages : 597

Book Description
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 Mathematical Optimization

Foundations of Mathematical Optimization PDF Author: Diethard Ernst Pallaschke
Publisher: Springer Science & Business Media
ISBN: 9401715882
Category : Mathematics
Languages : en
Pages : 597

Book Description
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
ISBN: 0387684077
Category : Business & Economics
Languages : en
Pages : 445

Book Description
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.

Foundations of Mathematical Optimization

Foundations of Mathematical Optimization PDF Author: Diethard Pallaschke
Publisher:
ISBN: 9789401715898
Category :
Languages : en
Pages : 600

Book Description


Practical Mathematical Optimization

Practical Mathematical Optimization PDF Author: Jan Snyman
Publisher: Springer Science & Business Media
ISBN: 0387243496
Category : Mathematics
Languages : en
Pages : 271

Book Description
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
ISBN: 1475757956
Category : Mathematics
Languages : en
Pages : 277

Book Description
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.

Mathematical Foundations of Nature-Inspired Algorithms

Mathematical Foundations of Nature-Inspired Algorithms PDF Author: Xin-She Yang
Publisher: Springer
ISBN: 3030169367
Category : Mathematics
Languages : en
Pages : 107

Book Description
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.

Foundations of Optimization

Foundations of Optimization PDF Author: M. S. Bazaraa
Publisher: Springer Science & Business Media
ISBN: 3642482945
Category : Business & Economics
Languages : en
Pages : 203

Book Description
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 Optimization and Economic Theory

Mathematical Optimization and Economic Theory PDF Author: Michael D. Intriligator
Publisher: SIAM
ISBN: 0898715113
Category : Mathematics
Languages : en
Pages : 515

Book Description
A classic account of mathematical programming and control techniques and their applications to static and dynamic problems in economics.

Foundations of Optimization

Foundations of Optimization PDF Author: Douglass J. Wilde
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 504

Book Description


Mathematics of Optimization: How to do Things Faster

Mathematics of Optimization: How to do Things Faster PDF Author: Steven J. Miller
Publisher: American Mathematical Soc.
ISBN: 1470441144
Category : Management science
Languages : en
Pages : 327

Book Description
Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the “why” and the “how” in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings.