Practical Mathematical Optimization

Author: Jan A Snyman
Publisher: Springer
ISBN: 3319775863
Format: PDF, Mobi
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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.

Practical Mathematical Optimization

Author: Jan Snyman
Publisher: Springer Science & Business Media
ISBN: 9780387243481
Format: PDF, Docs
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It is intended that this book be used in senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, com puter science and operations research departments. Hopefully this book will also be useful to practising professionals in the workplace. The contents of the book represent the fundamental optimization mate rial collected and used by the author, over a period of more than twenty years, in teaching Practical Mathematical Optimization to undergradu ate as well as graduate engineering and science students at the University of Pretoria. The principal motivation for writing this work has not been the teaching of mathematics per se, but to equip students with the nec essary fundamental optimization theory and algorithms, so as to enable them to solve practical problems in their own particular principal fields of interest, be it physics, chemistry, engineering design or business eco nomics. The particular approach adopted here follows from the author's own personal experiences in doing research in solid-state physics and in mechanical engineering design, where he was constantly confronted by problems that can most easily and directly be solved via the judicious use of mathematical optimization techniques. This book is, however, not a collection of case studies restricted to the above-mentioned specialized research areas, but is intended to convey the basic optimization princi ples and algorithms to a general audience in such a way that, hopefully, the application to their own practical areas of interest will be relatively simple and straightforward.

Mathematik und Technologie

Author: Christiane Rousseau
Publisher: Springer-Verlag
ISBN: 3642300928
Format: PDF, ePub, Mobi
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Zusammen mit der Abstraktion ist die Mathematik das entscheidende Werkzeug für technologische Innovationen. Das Buch bietet eine Einführung in zahlreiche Anwendungen der Mathematik auf dem Gebiet der Technologie. Meist werden moderne Anwendungen dargestellt, die heute zum Alltag gehören. Die mathematischen Grundlagen für technologische Anwendungen sind dabei relativ elementar, was die Leistungsstärke der mathematischen Modellbildung und der mathematischen Hilfsmittel beweist. Mit zahlreichen originellen Übungen am Ende eines jeden Kapitels.

Foundations of Computational Intelligence Volume 3

Author: Ajith Abraham
Publisher: Springer Science & Business Media
ISBN: 3642010849
Format: PDF
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Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc. Global Optimization algorithms may be categorized into several types: Deterministic (example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary algorithms) etc. Recently there has been a growing interest in combining global and local search strategies to solve more complicated optimization problems. This edited volume comprises 17 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of global optimization. Besides research articles and expository papers on theory and algorithms of global optimization, papers on numerical experiments and on real world applications were also encouraged. The book is divided into 2 main parts.

Numerische Verfahren der nichtlinearen Optimierung

Author: Peter Spellucci
Publisher: Springer-Verlag
ISBN: 3034872143
Format: PDF
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Dieses Lehrbuch bietet eine umfassende Darstellung derjenigen Verfahren zur Lösung nichtlinearer Optimierungsprobleme, die nach dem gegen- wärtigen Wissensstand als zuverlässig und effizient gelten. Es führt den Leser von den theoretischen Grundlagen bis auf den Stand der gegen- wärtigen Forschung. Dabei werden nur mathematische Vorkenntnisse vorausgesetzt, wie sie das Grundstudium sowohl für Mathematiker als auch für mathematisch orientierte Anwender üblicherweise bereitstellt. Neben einer sorgfältigen Erarbeitung der Konvergenzeigenschaften der Verfahren werden auch wichtige Details der Implementierung diskutiert. Das Buch enthält zahlreiche durchgerechnete Beispiele und Illustrationen, die dem Leser eine bessere Vorstellung über die Vorgehensweise und Leistungsfähigkeit der Verfahren vermitteln können. Zahlreiche Übungs- aufgaben verschiedenen Schwierigkeitsgrades ermöglichen dem Leser die Kontrolle seines Verständnisses. Das vorgelegte Werk geht sowohl in der Breite des behandelten Stoffes als auch in der Tiefe der mathematischen Analyse über die bestehenden Lehrbücher hinaus. Für die meisten Verfahren werden detailliert ausgearbeitete Konvergenzbeweise angegeben. Eine Fülle von Resultaten aus den letzten 10 Jahren erscheint hier zum ersten Mal in Buchform. Neben in Handrechnung nachvollziehbare einfache Beispiele treten ausgearbeitete Anwendungsbeispiele aus der Praxis.

Operations Research

Author: Frederick S. Hillier
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486792083
Format: PDF, Kindle
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Aus dem Vorwort der Autoren: “ bereits in früheren Auflagen sind uns auch bei dieser Auflage der Motivationscharakter und die Einfachheit der Ausführungen wichtiger als exakte Beweise und technische Freiheiten. Wir glauben, dass die vorliegende Auflage für den praxisorientierten Studenten, auch ohne große mathematische Kenntnisse, attraktiver und besser lesbar geworden ist. Dennoch sind wir der Meinung, dass die Theorie der Operations Research nur von der mathematischen Seite her wirklich verstanden und gewürdigt werden kann. Es ist daher auch die fünfte Auflage nach wie vor an den gleichen Leserkreis wie die früheren Auflagen gerichtet, an die Studenten verschiedenster Fachrichtungen (Ingenieurswesen, Wirtschafts- und Sozialwissenschaften sowie mathematische Wissenschaften), die sich manchmal angesichts des riesigen Wortschwalls ihrer Studiengebiete nach einem bißchen mathematischer Klarheit sehnen. Die einzelnen Kapitel lassen sich auf vielfältige Art und Weise zu Kursen oder zum Selbststudium zusammenstellen, da das Buch sehr flexibel angelegt ist. Teil eins liefert eine Einführung in die Thematik des Operations Research. Teil zwei (über lineare Programmierung) und auch Teil drei (über mathematische Programmierung) lassen sich unabhängig von Teil vier (über stochastische Modelle) durcharbeiten.“

Optimization Theory and Practice

Author: Wilhelm Forst
Publisher: Springer Science & Business Media
ISBN: 0387789766
Format: PDF, Docs
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Optimization is a field important in its own right but is also integral to numerous applied sciences, including operations research, management science, economics, finance and all branches of mathematics-oriented engineering. Constrained optimization models are one of the most widely used mathematical models in operations research and management science. This book gives a modern and well-balanced presentation of the subject, focusing on theory but also including algorithims and examples from various real-world applications. Detailed examples and counter-examples are provided--as are exercises, solutions and helpful hints, and Matlab/Maple supplements.

Data Mining Algorithms

Author: Pawel Cichosz
Publisher: John Wiley & Sons
ISBN: 1118950801
Format: PDF, Mobi
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Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

Linear and Nonlinear Optimization

Author: Richard W. Cottle
Publisher: Springer
ISBN: 1493970550
Format: PDF
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​This textbook on Linear and Nonlinear Optimization is intended for graduate and advanced undergraduate students in operations research and related fields. It is both literate and mathematically strong, yet requires no prior course in optimization. As suggested by its title, the book is divided into two parts covering in their individual chapters LP Models and Applications; Linear Equations and Inequalities; The Simplex Algorithm; Simplex Algorithm Continued; Duality and the Dual Simplex Algorithm; Postoptimality Analyses; Computational Considerations; Nonlinear (NLP) Models and Applications; Unconstrained Optimization; Descent Methods; Optimality Conditions; Problems with Linear Constraints; Problems with Nonlinear Constraints; Interior-Point Methods; and an Appendix covering Mathematical Concepts. Each chapter ends with a set of exercises. The book is based on lecture notes the authors have used in numerous optimization courses the authors have taught at Stanford University. It emphasizes modeling and numerical algorithms for optimization with continuous (not integer) variables. The discussion presents the underlying theory without always focusing on formal mathematical proofs (which can be found in cited references). Another feature of this book is its inclusion of cultural and historical matters, most often appearing among the footnotes. "This book is a real gem. The authors do a masterful job of rigorously presenting all of the relevant theory clearly and concisely while managing to avoid unnecessary tedious mathematical details. This is an ideal book for teaching a one or two semester masters-level course in optimization – it broadly covers linear and nonlinear programming effectively balancing modeling, algorithmic theory, computation, implementation, illuminating historical facts, and numerous interesting examples and exercises. Due to the clarity of the exposition, this book also serves as a valuable reference for self-study." Professor Ilan Adler, IEOR Department, UC Berkeley "A carefully crafted introduction to the main elements and applications of mathematical optimization. This volume presents the essential concepts of linear and nonlinear programming in an accessible format filled with anecdotes, examples, and exercises that bring the topic to life. The authors plumb their decades of experience in optimization to provide an enriching layer of historical context. Suitable for advanced undergraduates and masters students in management science, operations research, and related fields." Michael P. Friedlander, IBM Professor of Computer Science, Professor of Mathematics, University of British Columbia