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New Optimization Algorithms In Physics
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Book Synopsis New Optimization Algorithms in Physics by : Alexander K. Hartmann
Download or read book New Optimization Algorithms in Physics written by Alexander K. Hartmann and published by John Wiley & Sons. This book was released on 2006-03-06 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have not been presented comprehensively until now. This presentation of recently developed algorithms applied in physics, including demonstrations of how they work and related results, aims to encourage their application, and as such the algorithms selected cover concepts and methods from statistical physics to optimization problems emerging in theoretical computer science.
Book Synopsis Optimization Algorithms in Physics by : Alexander K. Hartmann
Download or read book Optimization Algorithms in Physics written by Alexander K. Hartmann and published by Wiley-VCH. This book was released on 2002-02-25 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few years have witnessed a substantial growth in the number of applications for optimization algorithms in solving problems in the field of physics. Examples include determining the structure of molecules, estimating the parameters of interacting galaxies, the ground states of electronic quantum systems, the behavior of disordered magnetic materials, and phase transitions in combinatorial optimization problems. This book serves as an introduction to the field, while also presenting a complete overview of modern algorithms. The authors begin with the relevant foundations from computer science, graph theory and statistical physics, before moving on to thoroughly explain algorithms - backed by illustrative examples. They include pertinent mathematical transformations, which in turn are used to make the physical problems tractable with methods from combinatorial optimization. Throughout, a number of interesting results are shown for all physical examples. The final chapter provides numerous practical hints on software development, testing programs, and evaluating the results of computer experiments.
Book Synopsis A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics by : Oscar Castillo
Download or read book A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics written by Oscar Castillo and published by Springer Nature. This book was released on 2021-08-18 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.
Book Synopsis Optimization Algorithms by : Jan Valdman
Download or read book Optimization Algorithms written by Jan Valdman and published by BoD – Books on Demand. This book was released on 2018-09-05 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents examples of modern optimization algorithms. The focus is on a clear understanding of underlying studied problems, understanding described algorithms by a broad range of scientists and providing (computational) examples that a reader can easily repeat.
Book Synopsis Optimization Algorithms on Matrix Manifolds by : P.-A. Absil
Download or read book Optimization Algorithms on Matrix Manifolds written by P.-A. Absil and published by Princeton University Press. This book was released on 2009-04-11 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms. It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction--illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development. In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis. It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists.
Author :Thomas Bartz-Beielstein Publisher :Springer Science & Business Media ISBN 13 :3642025382 Total Pages :469 pages Book Rating :4.6/5 (42 download)
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.
Book Synopsis Stochastic Optimization by : Johannes Schneider
Download or read book Stochastic Optimization written by Johannes Schneider and published by Springer Science & Business Media. This book was released on 2007-08-06 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses stochastic optimization procedures in a broad manner. The first part offers an overview of relevant optimization philosophies; the second deals with benchmark problems in depth, by applying a selection of optimization procedures. Written primarily with scientists and students from the physical and engineering sciences in mind, this book addresses a larger community of all who wish to learn about stochastic optimization techniques and how to use them.
Book Synopsis New Optimization Algorithms and their Applications by : Zhenxing Zhang
Download or read book New Optimization Algorithms and their Applications written by Zhenxing Zhang and published by Elsevier. This book was released on 2021-07-27 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: New Optimization Algorithms and Applications: Atom-Based, Ecosystem-Based and Economics-Based presents the development of three new optimization algorithms - an Atom Search Optimization (ASO) algorithm, an Artificial Ecosystem-Based Optimization algorithm (AEO), a Supply Demand Based Optimization (SDO), and their applications within engineering. These algorithms are based on benchmark functions and typical engineering cases. The book describes the algorithms in detail and demonstrates how to use them in engineering. The title verifies the performance of the algorithms presented, simulation results are given, and MATLAB® codes are provided for the methods described. Over seven chapters, the book introduces ASO, AEO and SDO, and presents benchmark functions, engineering problems, and coding. This volume offers technicians and researchers engaged in computer and intelligent algorithm work and engineering with one source of information on novel optimization algorithms. Presents three novel optimization algorithms for engineering Gives various applications and design examples for each algorithm Provides simulation results to verify algorithm performance Includes MATLAB® codes for optimization methods Describes the mathematical models needed
Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang
Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding as well as practical implementation hints - Provides a step-by-step introduction to each algorithm
Book Synopsis Practical Mathematical Optimization by : Jan Snyman
Download or read book Practical Mathematical Optimization written by Jan Snyman and published by Springer Science & Business Media. This book was released on 2005-12-15 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nature-Inspired Computing by : Nazmul H. Siddique
Download or read book Nature-Inspired Computing written by Nazmul H. Siddique and published by CRC Press. This book was released on 2017-05-19 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired computing, with an emphasis on applications to real-life engineering problems. The research interest for Nature-inspired Computing has grown considerably exploring different phenomena observed in nature and basic principles of physics, chemistry, and biology. The discipline has reached a mature stage and the field has been well-established. This endeavour is another attempt at investigation into various computational schemes inspired from nature, which are presented in this book with the development of a suitable framework and industrial applications. Designed for senior undergraduates, postgraduates, research students, and professionals, the book is written at a comprehensible level for students who have some basic knowledge of calculus and differential equations, and some exposure to optimization theory. Due to the focus on search and optimization, the book is also appropriate for electrical, control, civil, industrial and manufacturing engineering, business, and economics students, as well as those in computer and information sciences. With the mathematical and programming references and applications in each chapter, the book is self-contained, and can also serve as a reference for researchers and scientists in the fields of system science, natural computing, and optimization.
Book Synopsis Phase Transitions in Combinatorial Optimization Problems by : Alexander K. Hartmann
Download or read book Phase Transitions in Combinatorial Optimization Problems written by Alexander K. Hartmann and published by John Wiley & Sons. This book was released on 2006-05-12 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.
Book Synopsis Synthesis and Optimization of DSP Algorithms by : George Constantinides
Download or read book Synthesis and Optimization of DSP Algorithms written by George Constantinides and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synthesis and Optimization of DSP Algorithms describes approaches taken to synthesising structural hardware descriptions of digital circuits from high-level descriptions of Digital Signal Processing (DSP) algorithms. The book contains: -A tutorial on the subjects of digital design and architectural synthesis, intended for DSP engineers, -A tutorial on the subject of DSP, intended for digital designers, -A discussion of techniques for estimating the peak values likely to occur in a DSP system, thus enabling an appropriate signal scaling. Analytic techniques, simulation techniques, and hybrids are discussed. The applicability of different analytic approaches to different types of DSP design is covered, -The development of techniques to optimise the precision requirements of a DSP algorithm, aiming for efficient implementation in a custom parallel processor. The idea is to trade-off numerical accuracy for area or power-consumption advantages. Again, both analytic and simulation techniques for estimating numerical accuracy are described and contrasted. Optimum and heuristic approaches to precision optimisation are discussed, -A discussion of the importance of the scheduling, allocation, and binding problems, and development of techniques to automate these processes with reference to a precision-optimized algorithm, -Future perspectives for synthesis and optimization of DSP algorithms.
Book Synopsis New Optimization Techniques in Engineering by : Godfrey C. Onwubolu
Download or read book New Optimization Techniques in Engineering written by Godfrey C. Onwubolu and published by Springer. This book was released on 2013-03-14 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presently, general-purpose optimization techniques such as Simulated Annealing, and Genetic Algorithms, have become standard optimization techniques. Concerted research efforts have been made recently in order to invent novel optimization techniques for solving real life problems, which have the attributes of memory update and population-based search solutions. The book describes a variety of these novel optimization techniques which in most cases outperform the standard optimization techniques in many application areas. New Optimization Techniques in Engineering reports applications and results of the novel optimization techniques considering a multitude of practical problems in the different engineering disciplines – presenting both the background of the subject area and the techniques for solving the problems.
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.
Book Synopsis Large-Scale PDE-Constrained Optimization in Applications by : Subhendu Bikash Hazra
Download or read book Large-Scale PDE-Constrained Optimization in Applications written by Subhendu Bikash Hazra and published by Springer Science & Business Media. This book was released on 2009-12-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: With continuous development of modern computing hardware and applicable - merical methods, computational ?uid dynamics (CFD) has reached certain level of maturity so that it is being used routinely by scientists and engineers for ?uid ?ow analysis. Since most of the real-life applications involve some kind of optimization, it has been natural to extend the use of CFD tools from ?ow simulation to simu- tion based optimization. However, the transition from simulation to optimization is not straight forward, it requires proper interaction between advanced CFD meth- ologies and state-of-the-art optimization algorithms. The ultimate goal is to achieve optimal solution at the cost of few ?ow solutions. There is growing number of - search activities to achieve this goal. This book results from my work done on simulation based optimization problems at the Department of Mathematics, University of Trier, and reported in my postd- toral thesis (”Habilitationsschrift”) accepted by the Faculty-IV of this University in 2008. The focus of the work has been to develop mathematical methods and - gorithms which lead to ef?cient and high performance computational techniques to solve such optimization problems in real-life applications. Systematic development of the methods and algorithms are presented here. Practical aspects of implemen- tions are discussed at each level as the complexity of the problems increase, suppo- ing with enough number of computational examples.
Book Synopsis Teaching Learning Based Optimization Algorithm by : R. Venkata Rao
Download or read book Teaching Learning Based Optimization Algorithm written by R. Venkata Rao and published by Springer. This book was released on 2015-11-14 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.
