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Author: Xian Wen Ng
Publisher: Springer Nature
ISBN: 303084417X
Category : Technology & Engineering
Languages : en
Pages : 132
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Book Description
This concise text contains the most commonly-encountered examination problems in the topic of Optimization Models and Methods, an important module in engineering and other disciplines where there exists an increasing need to operate optimally and sustainably under constraints, such as tighter resource availability, environmental consideration, and cost pressures. This book is comprehensive in coverage as it includes a diverse spectrum of problems from numerical open-ended questions that probe creative thinking to the relation of concepts to realistic settings. The book adopts many examples of design scenarios as context for curating sample problems. This will help students relate desktop problem-solving to tackling real-world problems. Succinct yet rigorous, with over a 100 pages of problems and corresponding worked solutions presented in detail, the book is ideal for students of engineering, applied science, and market analysis.
Author: Xian Wen Ng
Publisher: Springer Nature
ISBN: 303084417X
Category : Technology & Engineering
Languages : en
Pages : 132
Get Book Here
Book Description
This concise text contains the most commonly-encountered examination problems in the topic of Optimization Models and Methods, an important module in engineering and other disciplines where there exists an increasing need to operate optimally and sustainably under constraints, such as tighter resource availability, environmental consideration, and cost pressures. This book is comprehensive in coverage as it includes a diverse spectrum of problems from numerical open-ended questions that probe creative thinking to the relation of concepts to realistic settings. The book adopts many examples of design scenarios as context for curating sample problems. This will help students relate desktop problem-solving to tackling real-world problems. Succinct yet rigorous, with over a 100 pages of problems and corresponding worked solutions presented in detail, the book is ideal for students of engineering, applied science, and market analysis.
Author: Xian Wen Ng
Publisher:
ISBN: 9783030844189
Category :
Languages : en
Pages : 0
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Book Description
This concise text contains the most commonly-encountered examination problems in the topic of Optimization Models and Methods, an important module in engineering and other disciplines where there exists an increasing need to operate optimally and sustainably under constraints, such as tighter resource availability, environmental consideration, and cost pressures. This book is comprehensive in coverage as it includes a diverse spectrum of problems from numerical open-ended questions that probe creative thinking to the relation of concepts to realistic settings. The book adopts many examples of design scenarios as context for curating sample problems. This will help students relate desktop problem-solving to tackling real-world problems. Succinct yet rigorous, with over a 100 pages of problems and corresponding worked solutions presented in detail, the book is ideal for students of engineering, applied science, and market analysis.
Author: John Lawrence Nazareth
Publisher: Springer Nature
ISBN: 3031217624
Category : Computers
Languages : en
Pages : 79
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Book Description
Numerical Algorithmic Science and Engineering (NAS&E), or more compactly, Numerical Algorithmics, is the theoretical and empirical study and the practical implementation and application of algorithms for solving finite-dimensional problems of a numeric nature. The variables of such problems are either discrete-valued, or continuous over the reals, or, and as is often the case, a combination of the two, and they may or may not have an underlying network/graph structure. This re-emerging discipline of numerical algorithmics within computer science is the counterpart of the now well-established discipline of numerical analysis within mathematics, where the latter’s emphasis is on infinite-dimensional, continuous numerical problems and their finite-dimensional, continuous approximates. A discussion of the underlying rationale for numerical algorithmics, its foundational models of computation, its organizational details, and its role, in conjunction with numerical analysis, in support of the modern modus operandi of scientific computing, or computational science & engineering, is the primary focus of this short monograph. It comprises six chapters, each with its own bibliography. Chapters 2, 3 and 6 present the book’s primary content. Chapters 1, 4, and 5 are briefer, and they provide contextual material for the three primary chapters and smooth the transition between them. Mathematical formalism has been kept to a minimum, and, whenever possible, visual and verbal forms of presentation are employed and the discussion enlivened through the use of motivating quotations and illustrative examples. The reader is expected to have a working knowledge of the basics of computer science, an exposure to basic linear algebra and calculus (and perhaps some real analysis), and an understanding of elementary mathematical concepts such as convexity of sets and functions, networks and graphs, and so on. Although this book is not suitable for use as the principal textbook for a course on numerical algorithmics (NAS&E), it will be of value as a supplementary reference for a variety of courses. It can also serve as the primary text for a research seminar. And it can be recommended for self-study of the foundations and organization of NAS&E to graduate and advanced undergraduate students with sufficient mathematical maturity and a background in computing. When departments of computer science were first created within universities worldwide during the middle of the twentieth century, numerical analysis was an important part of the curriculum. Its role within the discipline of computer science has greatly diminished over time, if not vanished altogether, and specialists in that area are now to be found mainly within other fields, in particular, mathematics and the physical sciences. A central concern of this monograph is the regrettable, downward trajectory of numerical analysis within computer science and how it can be arrested and suitably reconstituted. Resorting to a biblical metaphor, numerical algorithmics (NAS&E) as envisioned herein is neither old wine in new bottles, nor new wine in old bottles, but rather this re-emerging discipline is a decantation of an age-old vintage that can hopefully find its proper place within the larger arena of computer science, and at what appears now to be an opportune time.
Author: Gerard Cornuejols
Publisher: Cambridge University Press
ISBN: 9780521861700
Category : Mathematics
Languages : en
Pages : 358
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Book Description
Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.
Author: Xian Wen Ng
Publisher: Springer Nature
ISBN: 303083414X
Category : Science
Languages : en
Pages : 132
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Book Description
This book provides targeted support for students taking courses at the undergraduate level involving electrochemical methods and voltammetry, precision analytical techniques used in chemical engineering, chemical research and development, and pharmaceutical science. The learning method applied in this book, and the contents chosen, have been specifically tried-and-tested to support students preparing for exams, and for those having difficulty absorbing concepts and attaining an analytical understanding of their application. Through this book, “written for students by a student,” the author provides accessible learning resources that address students’ needs when preparing for examinations.
Author: John N. Hooker
Publisher: Springer Science & Business Media
ISBN: 146141900X
Category : Business & Economics
Languages : en
Pages : 655
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Book Description
The first edition of Integrated Methods for Optimization was published in January 2007. Because the book covers a rapidly developing field, the time is right for a second edition. The book provides a unified treatment of optimization methods. It brings ideas from mathematical programming (MP), constraint programming (CP), and global optimization (GO)into a single volume. There is no reason these must be learned as separate fields, as they normally are, and there are three reasons they should be studied together. (1) There is much in common among them intellectually, and to a large degree they can be understood as special cases of a single underlying solution technology. (2) A growing literature reports how they can be profitably integrated to formulate and solve a wide range of problems. (3) Several software packages now incorporate techniques from two or more of these fields. The book provides a unique resource for graduate students and practitioners who want a well-rounded background in optimization methods within a single course of study. Engineering students are a particularly large potential audience, because engineering optimization problems often benefit from a combined approach—particularly where design, scheduling, or logistics are involved. The text is also of value to those studying operations research, because their educational programs rarely cover CP, and to those studying computer science and artificial intelligence (AI), because their curric ula typically omit MP and GO. The text is also useful for practitioners in any of these areas who want to learn about another, because it provides a more concise and accessible treatment than other texts. The book can cover so wide a range of material because it focuses on ideas that arerelevant to the methods used in general-purpose optimization and constraint solvers. The book focuses on ideas behind the methods that have proved useful in general-purpose optimization and constraint solvers, as well as integrated solvers of the present and foreseeable future. The second edition updates results in this area and includes several major new topics: Background material in linear, nonlinear, and dynamic programming. Network flow theory, due to its importance in filtering algorithms. A chapter on generalized duality theory that more explicitly develops a unifying primal-dual algorithmic structure for optimization methods. An extensive survey of search methods from both MP and AI, using the primal-dual framework as an organizing principle. Coverage of several additional global constraints used in CP solvers. The book continues to focus on exact as opposed to heuristic methods. It is possible to bring heuristic methods into the unifying scheme described in the book, and the new edition will retain the brief discussion of how this might be done.
Author: Johannes Bisschop
Publisher: Lulu.com
ISBN: 1847539122
Category : Computers
Languages : en
Pages : 318
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Book Description
The AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent.
Author: Sheldon M. Ross
Publisher: Courier Corporation
ISBN: 0486318648
Category : Mathematics
Languages : en
Pages : 226
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Book Description
Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.
Author: Edmund K. Burke
Publisher: Springer Science & Business Media
ISBN: 1461469406
Category : Business & Economics
Languages : en
Pages : 715
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Book Description
The first edition of Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques was originally put together to offer a basic introduction to the various search and optimization techniques that students might need to use during their research, and this new edition continues this tradition. Search Methodologies has been expanded and brought completely up to date, including new chapters covering scatter search, GRASP, and very large neighborhood search. The chapter authors are drawn from across Computer Science and Operations Research and include some of the world’s leading authorities in their field. The book provides useful guidelines for implementing the methods and frameworks described and offers valuable tutorials to students and researchers in the field. “As I embarked on the pleasant journey of reading through the chapters of this book, I became convinced that this is one of the best sources of introductory material on the search methodologies topic to be found. The book’s subtitle, “Introductory Tutorials in Optimization and Decision Support Techniques”, aptly describes its aim, and the editors and contributors to this volume have achieved this aim with remarkable success. The chapters in this book are exemplary in giving useful guidelines for implementing the methods and frameworks described.” Fred Glover, Leeds School of Business, University of Colorado Boulder, USA “[The book] aims to present a series of well written tutorials by the leading experts in their fields. Moreover, it does this by covering practically the whole possible range of topics in the discipline. It enables students and practitioners to study and appreciate the beauty and the power of some of the computational search techniques that are able to effectively navigate through search spaces that are sometimes inconceivably large. I am convinced that this second edition will build on the success of the first edition and that it will prove to be just as popular.” Jacek Blazewicz, Institute of Computing Science, Poznan University of Technology and Institute of Bioorganic Chemistry, Polish Academy of Sciences
Author: Samuel B. Graves
Publisher: Springer Science & Business Media
ISBN: 1461502802
Category : Business & Economics
Languages : en
Pages : 203
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Book Description
Models & Methods for Project Selection systematically examines in this book treatment the latest work in the field of project selection modeling. The models presented are drawn from mathematical programming, decision theory, and finance. These models are examined in two categorical streams: the management science stream and the financial model stream. The book describes the assumptions and limitations of each model and provides appropriate solution methodologies. Its organization follows three main themes: *Criteria for Choice: Chapters 1-3 investigate the effect of the choice of optimization criteria on the results of the portfolio optimization problem. *Risk and Uncertainty: Chapters 4-7 deal with uncertainty in the project selection problem. *Non-Linearity and Interdependence: These chapters deal with problems of non-linearity and interdependence as they arise in the project selection problem. Chapters 8, 9 and 10 present solution methodologies, which can be used to solve these most general project selection models.
