New Optimization Algorithms In Physics

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New Optimization Algorithms in Physics

Alexander K. Hartmann,Heiko Rieger
New Optimization Algorithms in Physics Book PDF

Author : Alexander K. Hartmann,Heiko Rieger
Publisher : John Wiley & Sons
Page : 312 pages
File Size : 53,8 Mb
Release : 2006-03-06
Category : Science
ISBN : 9783527604579

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New Optimization Algorithms in Physics by Alexander K. Hartmann,Heiko Rieger Pdf

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.

Optimization Algorithms in Physics

Alexander K. Hartmann,Heiko Rieger
Optimization Algorithms in Physics Book PDF

Author : Alexander K. Hartmann,Heiko Rieger
Publisher : Wiley-VCH
Page : 382 pages
File Size : 47,5 Mb
Release : 2002-02-25
Category : Science
ISBN : 3527403078

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Optimization Algorithms in Physics by Alexander K. Hartmann,Heiko Rieger Pdf

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.

A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

Oscar Castillo,Luis Rodriguez
A New Meta heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics Book PDF

Author : Oscar Castillo,Luis Rodriguez
Publisher : Springer Nature
Page : 76 pages
File Size : 42,6 Mb
Release : 2021-08-18
Category : Technology & Engineering
ISBN : 9783030822880

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A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics by Oscar Castillo,Luis Rodriguez Pdf

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.

Optimization Algorithms

Jan Valdman
Optimization Algorithms Book PDF

Author : Jan Valdman
Publisher : BoD – Books on Demand
Page : 148 pages
File Size : 40,5 Mb
Release : 2018-09-05
Category : Mathematics
ISBN : 9781789236767

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Optimization Algorithms by Jan Valdman Pdf

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.

Particle Swarm Optimization

Alex Lazinica
Particle Swarm Optimization Book PDF

Author : Alex Lazinica
Publisher : BoD – Books on Demand
Page : 490 pages
File Size : 44,8 Mb
Release : 2009-01-01
Category : Computers
ISBN : 9789537619480

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Particle Swarm Optimization by Alex Lazinica Pdf

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field.

Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics

Thomas Stützle
Learning and Intelligent Optimization Designing Implementing and Analyzing Effective Heuristics Book PDF

Author : Thomas Stützle
Publisher : Springer Science & Business Media
Page : 284 pages
File Size : 49,9 Mb
Release : 2009-12-09
Category : Computers
ISBN : 9783642111686

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Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics by Thomas Stützle Pdf

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Learning and Intelligent Optimization, LION 2009 III, held in Trento, Italy, in January 2009. The 15 revised full papers, one extended abstract and two poster sessions were carefully reviewed and selected from 86 submissions for inclusion in the book. The papers cover current issues of stochastic local search methods and meta-heuristics, hybridizations of constraint and mathematical programming with meta-heuristics, supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search (online self-tuning methods), algorithm portfolios and off-line tuning methods, algorithms for dynamic, stochastic and multi-objective problems, interface(s) between discrete and continuous optimization, experimental analysis and modeling of algorithms, theoretical foundations, parallelization of optimization algorithms, memory-based optimization, prohibition-based methods (tabu search), memetic algorithms, evolutionary algorithms, dynamic local search, iterated local search, variable neighborhood search and swarm intelligence methods (ant colony optimization, particle swarm optimization etc.).

New Optimization Algorithms and their Applications

Zhenxing Zhang,Liying Wang,Weiguo Zhao
New Optimization Algorithms and their Applications Book PDF

Author : Zhenxing Zhang,Liying Wang,Weiguo Zhao
Publisher : Elsevier
Page : 180 pages
File Size : 47,9 Mb
Release : 2021-07-27
Category : Technology & Engineering
ISBN : 9780323909426

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New Optimization Algorithms and their Applications by Zhenxing Zhang,Liying Wang,Weiguo Zhao Pdf

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

New Optimization Techniques in Engineering

Godfrey C. Onwubolu,B. V. Babu
New Optimization Techniques in Engineering Book PDF

Author : Godfrey C. Onwubolu,B. V. Babu
Publisher : Springer
Page : 712 pages
File Size : 53,9 Mb
Release : 2013-03-14
Category : Technology & Engineering
ISBN : 9783540399308

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New Optimization Techniques in Engineering by Godfrey C. Onwubolu,B. V. Babu Pdf

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.

Particle Swarm Optimizaton

Said Mikki,Ahmed Kishk
Particle Swarm Optimizaton Book PDF

Author : Said Mikki,Ahmed Kishk
Publisher : Springer Nature
Page : 93 pages
File Size : 49,6 Mb
Release : 2022-06-01
Category : Technology & Engineering
ISBN : 9783031017049

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Particle Swarm Optimizaton by Said Mikki,Ahmed Kishk Pdf

This work aims to provide new introduction to the particle swarm optimization methods using a formal analogy with physical systems. By postulating that the swarm motion behaves similar to both classical and quantum particles, we establish a direct connection between what are usually assumed to be separate fields of study, optimization and physics. Within this framework, it becomes quite natural to derive the recently introduced quantum PSO algorithm from the Hamiltonian or the Lagrangian of the dynamical system. The physical theory of the PSO is used to suggest some improvements in the algorithm itself, like temperature acceleration techniques and the periodic boundary condition. At the end, we provide a panorama of applications demonstrating the power of the PSO, classical and quantum, in handling difficult engineering problems. The goal of this work is to provide a general multi-disciplinary view on various topics in physics, mathematics, and engineering by illustrating their interdependence within the unified framework of the swarm dynamics. Table of Contents: Introduction / The Classical Particle Swarm Optimization Method / Boundary Conditions for the PSO Method / The Quantum Particle Swarm Optimization / Bibliography /Index

Nature-Inspired Computing

Nazmul H. Siddique,Hojjat Adeli
Nature Inspired Computing Book PDF

Author : Nazmul H. Siddique,Hojjat Adeli
Publisher : CRC Press
Page : 616 pages
File Size : 50,5 Mb
Release : 2017-05-19
Category : Computers
ISBN : 9781351644914

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Nature-Inspired Computing by Nazmul H. Siddique,Hojjat Adeli Pdf

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.

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

Leslie Ann Goldberg,Klaus Jansen,R. Ravi,José D.P. Rolim
Approximation Randomization and Combinatorial Optimization Algorithms and Techniques Book PDF

Author : Leslie Ann Goldberg,Klaus Jansen,R. Ravi,José D.P. Rolim
Publisher : Springer Science & Business Media
Page : 715 pages
File Size : 48,5 Mb
Release : 2011-08-05
Category : Computers
ISBN : 9783642229343

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Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques by Leslie Ann Goldberg,Klaus Jansen,R. Ravi,José D.P. Rolim Pdf

This book constitutes the joint refereed proceedings of the 14th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2011, and the 15th International Workshop on Randomization and Computation, RANDOM 2011, held in Princeton, New Jersey, USA, in August 2011. The volume presents 29 revised full papers of the APPROX 2011 workshop, selected from 66 submissions, and 29 revised full papers of the RANDOM 2011 workshop, selected from 64 submissions. They were carefully reviewed and selected for inclusion in the book. In addition two abstracts of invited talks are included. APPROX focuses on algorithmic and complexity issues surrounding the development of efficient approximate solutions to computationally difficult problems. RANDOM is concerned with applications of randomness to computational and combinatorial problems.

Particle Swarm Optimizaton

Said M. Mikki,Ahmed A. Kishk
Particle Swarm Optimizaton Book PDF

Author : Said M. Mikki,Ahmed A. Kishk
Publisher : Morgan & Claypool Publishers
Page : 103 pages
File Size : 46,7 Mb
Release : 2008-08-08
Category : Technology & Engineering
ISBN : 9781598296150

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Particle Swarm Optimizaton by Said M. Mikki,Ahmed A. Kishk Pdf

This work aims to provide new introduction to the particle swarm optimization methods using a formal analogy with physical systems. By postulating that the swarm motion behaves similar to both classical and quantum particles, we establish a direct connection between what are usually assumed to be separate fields of study, optimization and physics. Within this framework, it becomes quite natural to derive the recently introduced quantum PSO algorithm from the Hamiltonian or the Lagrangian of the dynamical system. The physical theory of the PSO is used to suggest some improvements in the algorithm itself, like temperature acceleration techniques and the periodic boundary condition. At the end, we provide a panorama of applications demonstrating the power of the PSO, classical and quantum, in handling difficult engineering problems. The goal of this work is to provide a general multi-disciplinary view on various topics in physics, mathematics, and engineering by illustrating their interdependence within the unified framework of the swarm dynamics. Table of Contents: Introduction / The Classical Particle Swarm Optimization Method / Boundary Conditions for the PSO Method / The Quantum Particle Swarm Optimization / Bibliography /Index

Phase Transitions in Combinatorial Optimization Problems

Alexander K. Hartmann,Martin Weigt
Phase Transitions in Combinatorial Optimization Problems Book PDF

Author : Alexander K. Hartmann,Martin Weigt
Publisher : John Wiley & Sons
Page : 360 pages
File Size : 42,6 Mb
Release : 2006-05-12
Category : Science
ISBN : 9783527606863

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Phase Transitions in Combinatorial Optimization Problems by Alexander K. Hartmann,Martin Weigt Pdf

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.

Stochastic Optimization

Johannes Schneider,Scott Kirkpatrick
Stochastic Optimization Book PDF

Author : Johannes Schneider,Scott Kirkpatrick
Publisher : Springer Science & Business Media
Page : 551 pages
File Size : 41,6 Mb
Release : 2007-08-06
Category : Computers
ISBN : 9783540345602

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Stochastic Optimization by Johannes Schneider,Scott Kirkpatrick Pdf

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.

Experimental Methods for the Analysis of Optimization Algorithms

Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss
Experimental Methods for the Analysis of Optimization Algorithms Book PDF

Author : Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss
Publisher : Springer Science & Business Media
Page : 469 pages
File Size : 51,5 Mb
Release : 2010-11-02
Category : Computers
ISBN : 9783642025389

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Experimental Methods for the Analysis of Optimization Algorithms by Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss Pdf

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.