Fundamentals Of Optimization Techniques With Algorithms

Author : Sukanta Nayak
Publisher : Academic Press
Page : 323 pages
File Size : 40,6 Mb
Release : 2020-08-25
Category : Technology & Engineering
ISBN : 9780128224922

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Fundamentals of Optimization Techniques with Algorithms by Sukanta Nayak Pdf

Optimization 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 : Masanao Aoki
Publisher : Unknown
Page : 364 pages
File Size : 50,6 Mb
Release : 1971
Category : Mathematics
ISBN : UOM:39015004515766

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Introduction to Optimization Techniques by Masanao Aoki Pdf

Some mathematical preliminaries; Criterion function representation; Location problems; Minimization of unconstrained functions; Minimization of constrained functions; Duality in optimization problems; Comparisons of optimization methods and test problems.

Author : Ramteen Sioshansi,Antonio J. Conejo
Publisher : Springer
Page : 412 pages
File Size : 42,6 Mb
Release : 2017-06-24
Category : Mathematics
ISBN : 9783319567693

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Optimization in Engineering by Ramteen Sioshansi,Antonio J. Conejo Pdf

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.

Author : Xin-She Yang
Publisher : John Wiley & Sons
Page : 384 pages
File Size : 51,6 Mb
Release : 2018-09-19
Category : Mathematics
ISBN : 9781119490548

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Optimization Techniques and Applications with Examples by Xin-She Yang Pdf

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

Author : Douglass J. Wilde,Charles S. Beightler
Publisher : Unknown
Page : 504 pages
File Size : 47,5 Mb
Release : 1967
Category : Mathematical optimization
ISBN : UCAL:B3961759

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Foundations of Optimization by Douglass J. Wilde,Charles S. Beightler Pdf

Author : Stephen J. Wright,Benjamin Recht
Publisher : Cambridge University Press
Page : 239 pages
File Size : 54,5 Mb
Release : 2022-04-21
Category : Computers
ISBN : 9781316518984

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Optimization for Data Analysis by Stephen J. Wright,Benjamin Recht Pdf

A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

Author : Yong-Zai Lu,Yu-Wang Chen,Min-Rong Chen,Peng Chen,Guo-Qiang Zeng
Publisher : CRC Press
Page : 334 pages
File Size : 44,6 Mb
Release : 2016-04-21
Category : Computers
ISBN : 9781498705660

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Extremal Optimization by Yong-Zai Lu,Yu-Wang Chen,Min-Rong Chen,Peng Chen,Guo-Qiang Zeng Pdf

Extremal Optimization: Fundamentals, Algorithms, and Applications introduces state-of-the-art extremal optimization (EO) and modified EO (MEO) solutions from fundamentals, methodologies, and algorithms to applications based on numerous classic publications and the authors’ recent original research results. It promotes the movement of EO from academic study to practical applications. The book covers four aspects, beginning with a general review of real-world optimization problems and popular solutions with a focus on computational complexity, such as "NP-hard" and the "phase transitions" occurring on the search landscape. Next, it introduces computational extremal dynamics and its applications in EO from principles, mechanisms, and algorithms to the experiments on some benchmark problems such as TSP, spin glass, Max-SAT (maximum satisfiability), and graph partition. It then presents studies on the fundamental features of search dynamics and mechanisms in EO with a focus on self-organized optimization, evolutionary probability distribution, and structure features (e.g., backbones), which are based on the authors’ recent research results. Finally, it discusses applications of EO and MEO in multiobjective optimization, systems modeling, intelligent control, and production scheduling. The authors present the advanced features of EO in solving NP-hard problems through problem formulation, algorithms, and simulation studies on popular benchmarks and industrial applications. They also focus on the development of MEO and its applications. This book can be used as a reference for graduate students, research developers, and practical engineers who work on developing optimization solutions for those complex systems with hardness that cannot be solved with mathematical optimization or other computational intelligence, such as evolutionary computations.

Author : M. Asghar Bhatti
Publisher : Springer Science & Business Media
Page : 721 pages
File Size : 55,7 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461205012

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Practical Optimization Methods by M. Asghar Bhatti Pdf

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.

Author : B. Guenin,J. Könemann,L. Tunçel
Publisher : Cambridge University Press
Page : 283 pages
File Size : 53,8 Mb
Release : 2014-07-31
Category : Business & Economics
ISBN : 9781107053441

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A Gentle Introduction to Optimization by B. Guenin,J. Könemann,L. Tunçel Pdf

Assuming only basic linear algebra, this textbook is the perfect starting point for undergraduate students from across the mathematical sciences.

Author : Mykel J. Kochenderfer,Tim A. Wheeler
Publisher : MIT Press
Page : 521 pages
File Size : 40,6 Mb
Release : 2019-03-12
Category : Computers
ISBN : 9780262039420

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Algorithms for Optimization by Mykel J. Kochenderfer,Tim A. Wheeler Pdf

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Author : Jorge Nocedal,Stephen Wright
Publisher : Springer Science & Business Media
Page : 686 pages
File Size : 45,8 Mb
Release : 2006-12-11
Category : Mathematics
ISBN : 9780387400655

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Numerical Optimization by Jorge Nocedal,Stephen Wright Pdf

Optimization 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 : Rohollah Omidvar,Behrouz Minaei Bidgoli
Publisher : Bentham Science Publishers
Page : 209 pages
File Size : 47,7 Mb
Release : 2021-09-28
Category : Computers
ISBN : 9789811459573

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How to Design Optimization Algorithms by Applying Natural Behavioral Patterns by Rohollah Omidvar,Behrouz Minaei Bidgoli Pdf

How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference to students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena.

Author : Jan Snyman
Publisher : Springer Science & Business Media
Page : 282 pages
File Size : 46,6 Mb
Release : 2005-03-03
Category : Business & Economics
ISBN : 0387243488

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Practical Mathematical Optimization by Jan Snyman Pdf

This 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 : Ernesto G. Birgin,JosŸ Mario Martinez
Publisher : SIAM
Page : 222 pages
File Size : 55,6 Mb
Release : 2014-04-30
Category : Mathematics
ISBN : 9781611973358

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Practical Augmented Lagrangian Methods for Constrained Optimization by Ernesto G. Birgin,JosŸ Mario Martinez Pdf

This book focuses on Augmented Lagrangian techniques for solving practical constrained optimization problems. The authors rigorously delineate mathematical convergence theory based on sequential optimality conditions and novel constraint qualifications. They also orient the book to practitioners by giving priority to results that provide insight on the practical behavior of algorithms and by providing geometrical and algorithmic interpretations of every mathematical result, and they fully describe a freely available computational package for constrained optimization and illustrate its usefulness with applications.

Author : Rajesh Kumar Arora
Publisher : CRC Press
Page : 454 pages
File Size : 50,9 Mb
Release : 2015-05-06
Category : Business & Economics
ISBN : 9781498721158

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Optimization by Rajesh Kumar Arora Pdf

Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and co