Practical optimization methods : with Mathematica applications : CD-ROM included

(Telos) Textbook presenting basic optimization theory in a concise manner suitable for students in all branches of engineering, operations research, and management information systems. Approaches the subject from both a theoretical and mathematical style. The included CD-ROM contains software for the self-study problems. DLC: Mathematical optimization--Data processing. The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un­ dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use­ ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some­ where in between these two extremes is adopted in this book. Theory is pre­ sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de­ veloped in an informal style by appealing to readers'intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v'Preface VI -------------------------------------------------------- is presented. The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some where in between these two extremes is adopted in this book. Theory is pre sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de veloped in an informal style by appealing to readers' intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v ' Preface VI -- is presented "This book presents notions and ideas from the foundations of a statistical treatment of risks. Bayesian methods are frequently used in that area, hence a reasonable proportion of the presentation is devoted to such approaches. Modern statistical tools, namely Poisson regression, analysis of deviance, extreme-value theory and threshold methods are also used to identify and solve practical problems. The knowledge of such tools facilitates the understanding of the role of probability in risk analysis and proper use of outputs given by software packages." "The book is written with a student in mind who has studied elementary undergraduate courses in engineering mathematics, perhaps including an introductory course in statistics. The text emphasizes an understanding of the theory and methods presented. Hence, comments are given verbally and an intuitive reasoning is frequent. This is not just another new textbook on elementary probability and statistics, but focuses strongly on applications within the field of risk and safety analysis."--BOOK JACKET

this Introductory Textbook Presents Optimization Theory And Computational Algorithms Useful In Practice. The Approach Is Practical And Intuitive, Rather Than Emphasizing Mathematical Rigor. Computationally Oriented Books In This Area Generally Present Algorithms Alone, And Expect Readers To Perform Computations By Hand. Some Books Are Written In Traditional Computer Languages, Such As Basic, Fortran Or Pascal. The Programs In This Text Help With Computations. This Book Is The First Text To Use Mathematica To Develop Thorough Understanding Optimization Algorithms, Fully Exploiting Mathematica's Symbolic, Numerical And Graphic Capabilities.

This text presents notions and ideas at the foundations of a statistical treatment of risks. The focus is on statistical applications within the field of engineering risk and safety analysis. Coverage includes Bayesian methods. Such knowledge facilitates the understanding of the influence of random phenomena and gives a deeper understanding of the role of probability in risk analysis. The text is written for students who have studied elementary undergraduate courses in engineering mathematics, perhaps including a minor course in statistics. This book differs from typical textbooks in its verbal approach to many explanations and examples. This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities. This practical and intuitive introduction to optimization theory and computational algorithms features a cross-platform CD-ROM containing all the text, examples, "Mathematica 3.0" functions, and Notebooks. This is the first textbook to use "Mathematica" to develop a thorough understanding of optimization algorithms, fully exploiting "Mathematica's" symbolic, numerical, and graphical capabilities. 176 illus.