Experimental Methods for the Analysis of Optimization Algorithms
Experimental Methods for the Analysis of Optimization Algorithms

Author: Thomas Bartz-Beielstein

Publisher: Springer Science & Business Media

Published: 2010-11-02

Total Pages: 469

ISBN-13: 3642025382

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In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.

Computer Oriented Numerical and Statistical Methods
Computer Oriented Numerical and Statistical Methods

Author: SANT SHARAN MISHRA

Publisher: PHI Learning Pvt. Ltd.

Published: 2013-05-22

Total Pages: 512

ISBN-13: 8120347803

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This comprehensive text provides a thorough understanding of mathematical concepts and their applications with special emphasis on computational algorithms. The book gives a detailed discussion on all the relevant topics of both numerical and statistical methods, which are nowadays very important at computing level. It also includes the basic issues related to theory of estimation and testing of hypothesis, various sampling tests, and analysis of variance with plenty of illustrations. The topics covered in this book are supported by a large number of worked-out examples, C programs and algorithms to facilitate clear understanding of various theories discussed on numerical and statistical methods. The text is intended for the undergraduate students of computer engineering and postgraduate students of computer applications.

Statistical Optimization for Geometric Computation
Statistical Optimization for Geometric Computation

Author: Kenichi Kanatani

Publisher: Courier Corporation

Published: 2005-07-26

Total Pages: 548

ISBN-13: 0486443086

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This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. The numerous mathematical prerequisites for developing the theories are explained systematically in separate chapters. These methods range from linear algebra, optimization, and geometry to a detailed statistical theory of geometric patterns, fitting estimates, and model selection. In addition, examples drawn from both synthetic and real data demonstrate the insufficiencies of conventional procedures and the improvements in accuracy that result from the use of optimal methods.

Process Optimization
Process Optimization

Author: Enrique del Castillo

Publisher: Springer Science & Business Media

Published: 2007-09-14

Total Pages: 462

ISBN-13: 0387714359

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This book covers several bases at once. It is useful as a textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization, and more.

Introduction to Optimization Methods and their Application in Statistics
Introduction to Optimization Methods and their Application in Statistics

Author: B. Everitt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 87

ISBN-13: 9400931530

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Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.

Numerical Methods and Optimization
Numerical Methods and Optimization

Author: Sergiy Butenko

Publisher: CRC Press

Published: 2014-03-11

Total Pages: 415

ISBN-13: 1466577770

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For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods. Satisfying this prerequisite, Numerical Methods and Optimization: An Introduction combines the materials from introductory numerical methods and introductory optimization courses into a single text. This classroom-tested approach enriches a standard numerical methods syllabus with optional chapters on numerical optimization and provides a valuable numerical methods background for students taking an introductory OR or optimization course. The first part of the text introduces the necessary mathematical background, the digital representation of numbers, and different types of errors associated with numerical methods. The second part explains how to solve typical problems using numerical methods. Focusing on optimization methods, the final part presents basic theory and algorithms for linear and nonlinear optimization. The book assumes minimal prior knowledge of the topics. Taking a rigorous yet accessible approach to the material, it includes some mathematical proofs as samples of rigorous analysis but in most cases, uses only examples to illustrate the concepts. While the authors provide a MATLAB® guide and code available for download, the book can be used with other software packages.

Matrices
Matrices

Author: A. R. Vasishtha, A. K. Vasishtha

Publisher: Krishna Prakashan Media

Published:

Total Pages: 308

ISBN-13: 9788182830653

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