Introduction To Mathematical Optimization

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Author: Xin-She Yang
Publisher: Cambridge International Science Pub
ISBN: 9781904602828
Size: 47.52 MB
Format: PDF
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Introduction To Mathematical Optimization by Xin-She Yang


Original Title: Introduction To Mathematical Optimization

This book strives to provide a balanced coverage of efficient algorithms commonly used in solving mathematical optimization problems. It covers both the convectional algorithms and modern heuristic and metaheuristic methods. Topics include gradient-based algorithms such as Newton-Raphson method, steepest descent method, Hooke-Jeeves pattern search, Lagrange multipliers, linear programming, particle swarm optimization (PSO), simulated annealing (SA), and Tabu search. Multiobjective optimization including important concepts such as Pareto optimality and utility method is also described. Three Matlab and Octave programs so as to demonstrate how PSO and SA work are provided. An example of demonstrating how to modify these programs to solve multiobjective optimization problems using recursive method is discussed.

Numerical Analysis And Optimization

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Author: Grégoire Allaire
Publisher: Oxford University Press, USA
ISBN:
Size: 27.82 MB
Format: PDF, Mobi
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Numerical Analysis And Optimization by Grégoire Allaire


Original Title: Numerical Analysis And Optimization

Based on the Author's teaching notes at the Ecole Polytechnique,iNumerical Analysis and Optimization/i familiarises students with existingmathematical models (often partial differential equations) and their methods ofnumerical solution and optimization. The role of modelling and scientificcomputing has increased dramatically over recent years, and new applications ofmathematical models have emerged in Biology, Environmental Science, Finance,Medicine, and Social Science, as well as the classical applications inChemistry, Mechanics and Physics.Including numerous exercises and examples, this is an ideal text for advancedundergraduates and graduates and researchers in Applied Mathematics,Engineering, Computer Science, and the Physical Sciences.

Practical Mathematical Optimization

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Author: Jan Snyman
Publisher: Springer Science & Business Media
ISBN: 9780387243481
Size: 35.59 MB
Format: PDF, Mobi
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Practical Mathematical Optimization by Jan Snyman


Original Title: Practical Mathematical Optimization

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.

Introduction To Optimization

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Author: Pablo Pedregal
Publisher: Springer Science & Business Media
ISBN: 0387403981
Size: 31.15 MB
Format: PDF, ePub
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Introduction To Optimization by Pablo Pedregal


Original Title: Introduction To Optimization

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 Optimization

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Author: Edwin K. P. Chong
Publisher: John Wiley & Sons
ISBN: 1118515153
Size: 27.59 MB
Format: PDF, ePub
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An Introduction To Optimization by Edwin K. P. Chong


Original Title: An Introduction To Optimization

Praise for the Third Edition ". . . guides and leads the reader through the learning path . . . [e]xamples are stated very clearly and the results are presented with attention to detail." —MAA Reviews Fully updated to reflect new developments in the field, the Fourth Edition of Introduction to Optimization fills the need for accessible treatment of optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus. This new edition explores the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. Featuring an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, the Fourth Edition also offers: A new chapter on integer programming Expanded coverage of one-dimensional methods Updated and expanded sections on linear matrix inequalities Numerous new exercises at the end of each chapter MATLAB exercises and drill problems to reinforce the discussed theory and algorithms Numerous diagrams and figures that complement the written presentation of key concepts MATLAB M-files for implementation of the discussed theory and algorithms (available via the book's website) Introduction to Optimization, Fourth Edition is an ideal textbook for courses on optimization theory and methods. In addition, the book is a useful reference for professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.

Introduction To Applied Optimization

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Author: Urmila Diwekar
Publisher: Springer Science & Business Media
ISBN: 1475737459
Size: 47.68 MB
Format: PDF, ePub
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Introduction To Applied Optimization by Urmila Diwekar


Original Title: Introduction To Applied Optimization

This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.

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