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Author: Giuseppe C. Calafiore
Publisher: Cambridge University Press
Published: 2014-10-31
Total Pages: 651
ISBN-13: 1107050871
DOWNLOAD EBOOKThis accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.
Author: Jorge Nocedal
Publisher: Springer Science & Business Media
Published: 2006-12-11
Total Pages: 686
ISBN-13: 0387400656
DOWNLOAD EBOOKOptimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Author: Jan A Snyman
Publisher: Springer
Published: 2018-05-02
Total Pages: 388
ISBN-13: 3319775863
DOWNLOAD EBOOKThis 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.
Author: Mikulás Luptácik
Publisher: Springer Science & Business Media
Published: 2009-10-03
Total Pages: 299
ISBN-13: 0387895523
DOWNLOAD EBOOK"Mathematical Optimization and Economic Analysis" is a self-contained introduction to various optimization techniques used in economic modeling and analysis such as geometric, linear, and convex programming and data envelopment analysis. Through a systematic approach, this book demonstrates the usefulness of these mathematical tools in quantitative and qualitative economic analysis. The book presents specific examples to demonstrate each technique’s advantages and applicability as well as numerous applications of these techniques to industrial economics, regulatory economics, trade policy, economic sustainability, production planning, and environmental policy. Key Features include: - A detailed presentation of both single-objective and multiobjective optimization; - An in-depth exposition of various applied optimization problems; - Implementation of optimization tools to improve the accuracy of various economic models; - Extensive resources suggested for further reading. This book is intended for graduate and postgraduate students studying quantitative economics, as well as economics researchers and applied mathematicians. Requirements include a basic knowledge of calculus and linear algebra, and a familiarity with economic modeling.
Author: Jan Snyman
Publisher: Springer Science & Business Media
Published: 2005-12-15
Total Pages: 271
ISBN-13: 0387243496
DOWNLOAD EBOOKThis 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.
Author: Steven J. Miller
Publisher: American Mathematical Soc.
Published: 2017-12-20
Total Pages: 353
ISBN-13: 1470441144
DOWNLOAD EBOOKOptimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the “why” and the “how” in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings.
Author: Sukanta Nayak
Publisher: Academic Press
Published: 2020-08-25
Total Pages: 323
ISBN-13: 0128224924
DOWNLOAD EBOOKOptimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLAB© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice. - Presents optimization techniques clearly, including worked-out examples, from traditional to advanced - Maps out the relations between optimization and other mathematical topics and disciplines - Provides systematic coverage of algorithms to facilitate computer coding - Gives MATLAB© codes in relation to optimization techniques and their use in computer-aided design - Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks
Author: Robert Bosch (mathématicien)
Publisher: Princeton University Press
Published: 2019-11-12
Total Pages: 200
ISBN-13: 0691164061
DOWNLOAD EBOOKBosch provides a lively and accessible introduction to the geometric, algebraic, and algorithmic foundations of optimization. He presents classical applications, such as the legendary Traveling Salesman Problem, and shows how to adapt them to make optimization art--opt art. art.
Author: Andre A. Keller
Publisher: Academic Press
Published: 2017-11-10
Total Pages: 341
ISBN-13: 0128052953
DOWNLOAD EBOOKMathematical Optimization Terminology: A Comprehensive Glossary of Terms is a practical book with the essential formulations, illustrative examples, real-world applications and main references on the topic. This book helps readers gain a more practical understanding of optimization, enabling them to apply it to their algorithms. This book also addresses the need for a practical publication that introduces these concepts and techniques. - Discusses real-world applications of optimization and how it can be used in algorithms - Explains the essential formulations of optimization in mathematics - Covers a more practical approach to optimization
Author: Antonio J. Conejo
Publisher: Springer Science & Business Media
Published: 2006-04-28
Total Pages: 542
ISBN-13: 3540276866
DOWNLOAD EBOOKOptimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning procedure. For the sake of cl- ity, theoretical concepts and computational algorithms are assembled based on these examples. The results are simplicity, clarity, and easy-learning. We feel that this book is needed by the engineering community that has to tackle complex optimization problems, particularly by practitioners and researchersinEngineering,OperationsResearch,andAppliedEconomics.The descriptions of most decomposition techniques are available only in complex and specialized mathematical journals, di?cult to understand by engineers. A book describing a wide range of decomposition techniques, emphasizing problem-solving, and appropriately blending theory and application, was not previously available.
