Computational Optimization Methods And Algorithms

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Computational Optimization, Methods and Algorithms

Author : Slawomir Koziel
Publisher : Springer
ISBN 13 : 3642208592
Total Pages : 292 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Computational Optimization, Methods and Algorithms by : Slawomir Koziel

Download or read book Computational Optimization, Methods and Algorithms written by Slawomir Koziel and published by Springer. This book was released on 2011-06-17 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Computational Optimization, Methods and Algorithms

Author : Slawomir Koziel
Publisher : Springer Science & Business Media
ISBN 13 : 3642208584
Total Pages : 292 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Computational Optimization, Methods and Algorithms by : Slawomir Koziel

Download or read book Computational Optimization, Methods and Algorithms written by Slawomir Koziel and published by Springer Science & Business Media. This book was released on 2011-06-17 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Feasibility and Infeasibility in Optimization:

Author : John W. Chinneck
Publisher : Springer Science & Business Media
ISBN 13 : 0387749322
Total Pages : 283 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Feasibility and Infeasibility in Optimization: by : John W. Chinneck

Download or read book Feasibility and Infeasibility in Optimization: written by John W. Chinneck and published by Springer Science & Business Media. This book was released on 2007-10-25 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.

Algorithms for Optimization

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262039427
Total Pages : 521 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Algorithms for Optimization by : Mykel J. Kochenderfer

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Optimization Techniques and Applications

Author : Muhammad Sarfraz
Publisher : BoD – Books on Demand
ISBN 13 : 1839687657
Total Pages : 245 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Computational Optimization Techniques and Applications by : Muhammad Sarfraz

Download or read book Computational Optimization Techniques and Applications written by Muhammad Sarfraz and published by BoD – Books on Demand. This book was released on 2021-08-25 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational optimization is an active and important area of study, practice, and research today. It covers a wide range of applications in engineering, science, and industry. It provides solutions to a variety of real-life problems in the fields of health, business, government, military, politics, security, education, and many more. This book compiles original and innovative findings on all aspects of computational optimization. It presents various examples of optimization including cost, energy, profits, outputs, performance, and efficiency. It also discusses different types of optimization problems like nonlinearity, multimodality, discontinuity, and uncertainty. Over thirteen chapters, the book provides researchers, practitioners, academicians, military professionals, government officials, and other industry professionals with an in-depth discussion of the latest advances in the field.

Experimental Methods for the Analysis of Optimization Algorithms

Author : Thomas Bartz-Beielstein
Publisher : Springer Science & Business Media
ISBN 13 : 3642025382
Total Pages : 469 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Experimental Methods for the Analysis of Optimization Algorithms by : Thomas Bartz-Beielstein

Download or read book Experimental Methods for the Analysis of Optimization Algorithms written by Thomas Bartz-Beielstein and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Optimization and Applications in Engineering and Industry

Author : Xin-She Yang
Publisher : Springer
ISBN 13 : 3642209866
Total Pages : 282 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Computational Optimization and Applications in Engineering and Industry by : Xin-She Yang

Download or read book Computational Optimization and Applications in Engineering and Industry written by Xin-She Yang and published by Springer. This book was released on 2011-06-19 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contemporary design in engineering and industry relies heavily on computer simulation and efficient algorithms to reduce the cost and to maximize the performance and sustainability as well as profits and energy efficiency. Solving an optimization problem correctly and efficiently requires not only the right choice of optimization algorithms and simulation methods, but also the proper implementation and insight into the problem of interest. This book consists of ten self-contained, detailed case studies of real-world optimization problems, selected from a wide range of applications and contributed from worldwide experts who are working in these exciting areas. Optimization topics and applications include gas and water supply networks, oil field production optimization, microwave engineering, aerodynamic shape design, environmental emergence modelling, structural engineering, waveform design for radar and communication systems, parameter estimation in laser experiment and measurement, engineering materials and network scheduling. These case studies have been solved using a wide range of optimization techniques, including particle swarm optimization, genetic algorithms, artificial bee colony, harmony search, adaptive error control, derivative-free pattern search, surrogate-based optimization, variable-fidelity modelling, as well as various other methods and approaches. This book is a practical guide to help graduates and researchers to carry out optimization for real-world applications. More advanced readers will also find it a helpful reference and aide memoire.

Bioinspired Computation in Combinatorial Optimization

Author : Frank Neumann
Publisher : Springer Science & Business Media
ISBN 13 : 3642165443
Total Pages : 215 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Bioinspired Computation in Combinatorial Optimization by : Frank Neumann

Download or read book Bioinspired Computation in Combinatorial Optimization written by Frank Neumann and published by Springer Science & Business Media. This book was released on 2010-11-04 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.

Computational Optimization in Engineering

Author : Hossein Peyvandi
Publisher : BoD – Books on Demand
ISBN 13 : 9535130811
Total Pages : 164 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Computational Optimization in Engineering by : Hossein Peyvandi

Download or read book Computational Optimization in Engineering written by Hossein Peyvandi and published by BoD – Books on Demand. This book was released on 2017-04-26 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of optimization is to maximize the quality of lives, productivity in time, as well as interests. Therefore, optimization is an ongoing challenge for selecting the best possible among many other inferior designs. For a hundred years in the past, as optimization has been essential to human life, several techniques have been developed and utilized. Such a development has been one of the long-lasting challenges in engineering and science, and it is now clear that the optimization goals in many of real-life problems are unlikely to be achieved without resource for computational techniques. The history of such a development in the optimization techniques starts from the early 1950s and is still in progress. Since then, the efforts behind this development dedicated by many distinguished scientists, mathematicians, and engineers have brought us today a level of quality of lives. This book concerns with the computational optimization in engineering and techniques to resolve the underlying problems in real life. The current book contains studies from scientists and researchers around the world from North America to Europe and from Asia to Australia.

Recent Advances in Computational Optimization

Author : Stefka Fidanova
Publisher : Springer
ISBN 13 : 9783030823993
Total Pages : 0 pages
Book Rating : 4.8/5 (239 download)

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Book Synopsis Recent Advances in Computational Optimization by : Stefka Fidanova

Download or read book Recent Advances in Computational Optimization written by Stefka Fidanova and published by Springer. This book was released on 2022-12-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in computational optimization. Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2020. The book includes important real problems like modeling of physical processes, workforce planning, parameter settings for controlling different processes, transportation problems, wireless sensor networks, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential equations which describe real processes, solving engineering problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.

Optimization

Author : Rajesh Kumar Arora
Publisher : CRC Press
ISBN 13 : 149872115X
Total Pages : 454 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Optimization by : Rajesh Kumar Arora

Download or read book Optimization written by Rajesh Kumar Arora and published by CRC Press. This book was released on 2015-05-06 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Recent Advances in Computational Optimization

Author : Stefka Fidanova
Publisher : Springer
ISBN 13 : 3319996487
Total Pages : 239 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Recent Advances in Computational Optimization by : Stefka Fidanova

Download or read book Recent Advances in Computational Optimization written by Stefka Fidanova and published by Springer. This book was released on 2018-09-18 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our everyday lives are practically unthinkable without optimization. We constantly try to minimize our effort and to maximize the reward or progress achieved. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume presents a comprehensive collection of extended contributions from the 2017 Workshop on Computational Optimization. Presenting recent advances in computational optimization, it addresses important concrete applications, e.g. the modeling of physical processes, wildfire modeling, modeling processes in chemical engineering, workforce planning, wireless access network topology, parameter settings for controlling various processes, berth allocation, identification of homogeneous domains, and quantum computing. The book shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others.

Fundamentals of Optimization Techniques with Algorithms

Author : Sukanta Nayak
Publisher : Academic Press
ISBN 13 : 0128224924
Total Pages : 323 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Fundamentals of Optimization Techniques with Algorithms by : Sukanta Nayak

Download or read book Fundamentals of Optimization Techniques with Algorithms written by Sukanta Nayak and published by Academic Press. This book was released on 2020-08-25 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Introduction to Optimization Methods

Author : P. Adby
Publisher : Springer Science & Business Media
ISBN 13 : 940095705X
Total Pages : 214 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Introduction to Optimization Methods by : P. Adby

Download or read book Introduction to Optimization Methods written by P. Adby and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade the techniques of non-linear optim ization have emerged as an important subject for study and research. The increasingly widespread application of optim ization has been stimulated by the availability of digital computers, and the necessity of using them in the investigation of large systems. This book is an introduction to non-linear methods of optimization and is suitable for undergraduate and post graduate courses in mathematics, the physical and social sciences, and engineering. The first half of the book covers the basic optimization techniques including linear search methods, steepest descent, least squares, and the Newton-Raphson method. These are described in detail, with worked numerical examples, since they form the basis from which advanced methods are derived. Since 1965 advanced methods of unconstrained and constrained optimization have been developed to utilise the computational power of the digital computer. The second half of the book describes fully important algorithms in current use such as variable metric methods for unconstrained problems and penalty function methods for constrained problems. Recent work, much of which has not yet been widely applied, is reviewed and compared with currently popular techniques under a few generic main headings. vi PREFACE Chapter I describes the optimization problem in mathemat ical form and defines the terminology used in the remainder of the book. Chapter 2 is concerned with single variable optimization. The main algorithms of both search and approximation methods are developed in detail since they are an essential part of many multi-variable methods.

Algorithms for Convex Optimization

Author : Nisheeth K. Vishnoi
Publisher : Cambridge University Press
ISBN 13 : 1108633994
Total Pages : 314 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Algorithms for Convex Optimization by : Nisheeth K. Vishnoi

Download or read book Algorithms for Convex Optimization written by Nisheeth K. Vishnoi and published by Cambridge University Press. This book was released on 2021-10-07 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.

Optimization Algorithms

Author : Ozgur Baskan
Publisher : BoD – Books on Demand
ISBN 13 : 9535125923
Total Pages : 326 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Optimization Algorithms by : Ozgur Baskan

Download or read book Optimization Algorithms written by Ozgur Baskan and published by BoD – Books on Demand. This book was released on 2016-09-21 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers state-of-the-art optimization methods and their applications in wide range especially for researchers and practitioners who wish to improve their knowledge in this field. It consists of 13 chapters divided into two parts: (I) Engineering applications, which presents some new applications of different methods, and (II) Applications in various areas, where recent contributions of state-of-the-art optimization methods to diverse fields are presented.

Computational Intelligence for Optimization

Author : Nirwan Ansari
Publisher : Springer Science & Business Media
ISBN 13 : 1461563313
Total Pages : 228 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Computational Intelligence for Optimization by : Nirwan Ansari

Download or read book Computational Intelligence for Optimization written by Nirwan Ansari and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.