Stochastic Search Algorithms

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Stochastic Local Search

Holger H. Hoos,Thomas Stützle
Stochastic Local Search Book PDF

Author : Holger H. Hoos,Thomas Stützle
Publisher : Morgan Kaufmann
Page : 678 pages
File Size : 55,6 Mb
Release : 2005
Category : Business & Economics
ISBN : 9781558608726

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Stochastic Local Search by Holger H. Hoos,Thomas Stützle Pdf

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Bioinspired Computation in Combinatorial Optimization

Frank Neumann,Carsten Witt
Bioinspired Computation in Combinatorial Optimization Book PDF

Author : Frank Neumann,Carsten Witt
Publisher : Springer Science & Business Media
Page : 215 pages
File Size : 53,9 Mb
Release : 2010-11-04
Category : Mathematics
ISBN : 9783642165443

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Bioinspired Computation in Combinatorial Optimization by Frank Neumann,Carsten Witt Pdf

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.

Introduction to Stochastic Search and Optimization

James C. Spall
Introduction to Stochastic Search and Optimization Book PDF

Author : James C. Spall
Publisher : John Wiley & Sons
Page : 620 pages
File Size : 47,6 Mb
Release : 2005-03-11
Category : Mathematics
ISBN : 9780471441908

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Introduction to Stochastic Search and Optimization by James C. Spall Pdf

* Unique in its survey of the range of topics. * Contains a strong, interdisciplinary format that will appeal to both students and researchers. * Features exercises and web links to software and data sets.

Stochastic Recursive Algorithms for Optimization

S. Bhatnagar,H.L. Prasad,L.A. Prashanth
Stochastic Recursive Algorithms for Optimization Book PDF

Author : S. Bhatnagar,H.L. Prasad,L.A. Prashanth
Publisher : Springer
Page : 310 pages
File Size : 49,7 Mb
Release : 2012-08-11
Category : Technology & Engineering
ISBN : 9781447142850

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Stochastic Recursive Algorithms for Optimization by S. Bhatnagar,H.L. Prasad,L.A. Prashanth Pdf

Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms: • are easily implemented; • do not require an explicit system model; and • work with real or simulated data. Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix. The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.

Stochastic Adaptive Search for Global Optimization

Z.B. Zabinsky
Stochastic Adaptive Search for Global Optimization Book PDF

Author : Z.B. Zabinsky
Publisher : Springer Science & Business Media
Page : 236 pages
File Size : 48,7 Mb
Release : 2013-11-27
Category : Mathematics
ISBN : 9781441991829

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Stochastic Adaptive Search for Global Optimization by Z.B. Zabinsky Pdf

The field of global optimization has been developing at a rapid pace. There is a journal devoted to the topic, as well as many publications and notable books discussing various aspects of global optimization. This book is intended to complement these other publications with a focus on stochastic methods for global optimization. Stochastic methods, such as simulated annealing and genetic algo rithms, are gaining in popularity among practitioners and engineers be they are relatively easy to program on a computer and may be cause applied to a broad class of global optimization problems. However, the theoretical performance of these stochastic methods is not well under stood. In this book, an attempt is made to describe the theoretical prop erties of several stochastic adaptive search methods. Such a theoretical understanding may allow us to better predict algorithm performance and ultimately design new and improved algorithms. This book consolidates a collection of papers on the analysis and de velopment of stochastic adaptive search. The first chapter introduces random search algorithms. Chapters 2-5 describe the theoretical anal ysis of a progression of algorithms. A main result is that the expected number of iterations for pure adaptive search is linear in dimension for a class of Lipschitz global optimization problems. Chapter 6 discusses algorithms, based on the Hit-and-Run sampling method, that have been developed to approximate the ideal performance of pure random search. The final chapter discusses several applications in engineering that use stochastic adaptive search methods.

Stochastic Local Search

Holger H. Hoos,Thomas Stützle
Stochastic Local Search Book PDF

Author : Holger H. Hoos,Thomas Stützle
Publisher : Elsevier
Page : 677 pages
File Size : 42,9 Mb
Release : 2004-09-28
Category : Computers
ISBN : 9780080498249

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Stochastic Local Search by Holger H. Hoos,Thomas Stützle Pdf

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. Provides the first unified view of the field Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms

Stochastic Approximation and Recursive Algorithms and Applications

Harold Kushner,G. George Yin
Stochastic Approximation and Recursive Algorithms and Applications Book PDF

Author : Harold Kushner,G. George Yin
Publisher : Springer Science & Business Media
Page : 485 pages
File Size : 54,7 Mb
Release : 2006-05-04
Category : Mathematics
ISBN : 9780387217697

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Stochastic Approximation and Recursive Algorithms and Applications by Harold Kushner,G. George Yin Pdf

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion.

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 : 47,5 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.

Stochastic Optimization

Stanislav Uryasev,Panos M. Pardalos
Stochastic Optimization Book PDF

Author : Stanislav Uryasev,Panos M. Pardalos
Publisher : Springer Science & Business Media
Page : 438 pages
File Size : 45,5 Mb
Release : 2013-03-09
Category : Technology & Engineering
ISBN : 9781475765946

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Stochastic Optimization by Stanislav Uryasev,Panos M. Pardalos Pdf

Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic programming applications and other related topics. Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.

First-order and Stochastic Optimization Methods for Machine Learning

Guanghui Lan
First order and Stochastic Optimization Methods for Machine Learning Book PDF

Author : Guanghui Lan
Publisher : Springer Nature
Page : 591 pages
File Size : 46,8 Mb
Release : 2020-05-15
Category : Mathematics
ISBN : 9783030395681

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First-order and Stochastic Optimization Methods for Machine Learning by Guanghui Lan Pdf

This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.

Stochastic Algorithms for Visual Tracking

John MacCormick
Stochastic Algorithms for Visual Tracking Book PDF

Author : John MacCormick
Publisher : Springer Science & Business Media
Page : 184 pages
File Size : 53,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447106791

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Stochastic Algorithms for Visual Tracking by John MacCormick Pdf

A central problem in computer vision is to track objects as they move and deform in a video sequence. Stochastic algorithms -- in particular, particle filters and the Condensation algorithm -- have dramatically enhanced the state of the art for such visual tracking problems in recent years. This book presents a unified framework for visual tracking using particle filters, including the new technique of partitioned sampling which can alleviate the "curse of dimensionality" suffered by standard particle filters. The book also introduces the notion of contour likelihood: a collection of models for assessing object shape, colour and motion, which are derived from the statistical properties of image features. Because of their statistical nature, contour likelihoods are ideal for use in stochastic algorithms. A unifying theme of the book is the use of statistics and probability, which enable the final output of the algorithms presented to be interpreted as the computer's "belief" about the state of the world. The book will be of use and interest to students, researchers and practitioners in computer vision, and assumes only an elementary knowledge of probability theory.

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 : 40,5 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.

Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization

Luis F. Paquete
Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization Book PDF

Author : Luis F. Paquete
Publisher : IOS Press
Page : 394 pages
File Size : 51,9 Mb
Release : 2006
Category : Business & Economics
ISBN : 1586035967

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Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization by Luis F. Paquete Pdf

Stochastic Local Search algorithms were shown to give state-of-the-art results for many other problems, but little is known on how to design and analyse them for Multiobjective Combinatorial Optimization Problems. This book aims to fill this gap. It defines two search models that correspond to two distinct ways of tackling MCOPs by SLS algorithms."

Stochastic Algorithms: Foundations and Applications

Andreas Albrecht,Kathleen Steinhöfel
Stochastic Algorithms Foundations and Applications Book PDF

Author : Andreas Albrecht,Kathleen Steinhöfel
Publisher : Springer
Page : 176 pages
File Size : 43,7 Mb
Release : 2003-11-20
Category : Mathematics
ISBN : 9783540398165

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Stochastic Algorithms: Foundations and Applications by Andreas Albrecht,Kathleen Steinhöfel Pdf

This book constitutes the refereed proceedings of the Second International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2003, held in Hatfield, UK in September 2003. The 12 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the book. Among the topics addressed are ant colony optimization, randomized algorithms for the intersection problem, local search for constraint satisfaction problems, randomized local search and combinatorial optimization, simulated annealing, probabilistic global search, network communication complexity, open shop scheduling, aircraft routing, traffic control, randomized straight-line programs, and stochastic automata and probabilistic transformations.

Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics

Thomas Stützle,Mauro Birattari,Holger H. Hoos
Engineering Stochastic Local Search Algorithms Designing Implementing and Analyzing Effective Heuristics Book PDF

Author : Thomas Stützle,Mauro Birattari,Holger H. Hoos
Publisher : Springer
Page : 230 pages
File Size : 52,9 Mb
Release : 2007-08-22
Category : Computers
ISBN : 9783540744467

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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics by Thomas Stützle,Mauro Birattari,Holger H. Hoos Pdf

This volume constitutes the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms. Inside the volume, readers will find twelve full papers as well as nine short papers. Topics include methodological developments, behavior of SLS algorithms, search space analysis, algorithm performance, tuning procedures, AI/OR techniques, and dynamic behavior.