Stochastic Global Optimization

Stochastic Global Optimization
Author: Anatoly Zhigljavsky
Publisher: Springer Science & Business Media
Total Pages: 269
Release: 2007-11-20
Genre: Mathematics
ISBN: 0387747400

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This book examines the main methodological and theoretical developments in stochastic global optimization. It is designed to inspire readers to explore various stochastic methods of global optimization by clearly explaining the main methodological principles and features of the methods. Among the book’s features is a comprehensive study of probabilistic and statistical models underlying the stochastic optimization algorithms.

Stochastic Global Optimization

Stochastic Global Optimization
Author: Gade Pandu Rangaiah
Publisher: World Scientific
Total Pages: 722
Release: 2010
Genre: Computers
ISBN: 9814299219

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Ch. 1. Introduction / Gade Pandu Rangaiah -- ch. 2. Formulation and illustration of Luus-Jaakola optimization procedure / Rein Luus -- ch. 3. Adaptive random search and simulated annealing optimizers : algorithms and application issues / Jacek M. Jezowski, Grzegorz Poplewski and Roman Bochenek -- ch. 4. Genetic algorithms in process engineering : developments and implementation issues / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 5. Tabu search for global optimization of problems having continuous variables / Sim Mong Kai, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 6. Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. Jayaraman [und weitere] -- ch. 8. Particle swarm optimization for solving NLP and MINLP in chemical engineering / Bassem Jarboui [und weitere] -- ch. 9. An introduction to the harmony search algorithm / Gordon Ingram and Tonghua Zhang -- ch. 10. Meta-heuristics : evaluation and reporting techniques / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 11. A hybrid approach for constraint handling in MINLP optimization using stochastic algorithms / G.A. Durand [und weitere] -- ch. 12. Application of Luus-Jaakola optimization procedure to model reduction, parameter estimation and optimal control / Rein Luus -- ch. 13. Phase stability and equilibrium calculations in reactive systems using differential evolution and tabu search / Adrian Bonilla-Petriciolet [und weitere] -- ch. 14. Differential evolution with tabu list for global optimization : evaluation of two versions on benchmark and phase stability problems / Mekapati Srinivas and Gade Pandu Rangaiah -- ch. 15. Application of adaptive random search optimization for solving industrial water allocation problem / Grzegorz Poplewski and Jacek M. Jezowski -- ch. 16. Genetic algorithms formulation for retrofitting heat exchanger network / Roman Bochenek and Jacek M. Jezowski -- ch. 17. Ant colony optimization for classification and feature selection / V.K. Jayaraman [und weitere] -- ch. 18. Constraint programming and genetic algorithm / Prakash R. Kotecha, Mani Bhushan and Ravindra D. Gudi -- ch. 19. Schemes and implementations of parallel stochastic optimization algorithms application of tabu search to chemical engineering problems / B. Lin and D.C. Miller

Stochastic Adaptive Search for Global Optimization

Stochastic Adaptive Search for Global Optimization
Author: Z.B. Zabinsky
Publisher: Springer Science & Business Media
Total Pages: 236
Release: 2013-11-27
Genre: Mathematics
ISBN: 1441991824

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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 Optimization

Stochastic Optimization
Author: Johannes Schneider
Publisher: Springer Science & Business Media
Total Pages: 551
Release: 2007-08-06
Genre: Computers
ISBN: 3540345604

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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 and Global Optimization

Stochastic and Global Optimization
Author: G. Dzemyda
Publisher: Springer Science & Business Media
Total Pages: 238
Release: 2002-03-31
Genre: Computers
ISBN: 1402004842

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This book is dedicated to the 70th birthday of Professor J. Mockus, whose scientific interests include theory and applications of global and discrete optimization, and stochastic programming. The papers for the book were selected because they relate to these topics and also satisfy the criterion of theoretical soundness combined with practical applicability. In addition, the methods for statistical analysis of extremal problems are covered. Although statistical approach to global and discrete optimization is emphasized, applications to optimal design and to mathematical finance are also presented. The results of some subjects (e.g., statistical models based on one-dimensional global optimization) are summarized and the prospects for new developments are justified. Audience: Practitioners, graduate students in mathematics, statistics, computer science and engineering.

Stochastic and Global Optimization

Stochastic and Global Optimization
Author: G. Dzemyda
Publisher: Springer Science & Business Media
Total Pages: 238
Release: 2006-04-11
Genre: Mathematics
ISBN: 0306476487

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In the paper we propose a model of tax incentives optimization for inve- ment projects with a help of the mechanism of accelerated depreciation. Unlike the tax holidays which influence on effective income tax rate, accelerated - preciation affects on taxable income. In modern economic practice the state actively use for an attraction of - vestment into the creation of new enterprises such mechanisms as accelerated depreciation and tax holidays. The problem under our consideration is the following. Assume that the state (region) is interested in realization of a certain investment project, for ex- ple, the creation of a new enterprise. In order to attract a potential investor the state decides to use a mechanism of accelerated tax depreciation. The foll- ing question arise. What is a reasonable principle for choosing depreciation rate? From the state’s point of view the future investor’s behavior will be rat- nal. It means that while looking at economic environment the investor choose such a moment for investment which maximizes his expected net present value (NPV) from the given project. For this case both criteria and “investment rule” depend on proposed (by the state) depreciation policy. For the simplicity we will suppose that the purpose of the state for a given project is a maximi- tion of a discounted tax payments into the budget from the enterprise after its creation. Of course, these payments depend on the moment of investor’s entry and, therefore, on the depreciation policy established by the state.

Stochastic Optimization Methods

Stochastic Optimization Methods
Author: Kurt Marti
Publisher: Springer
Total Pages: 389
Release: 2015-02-21
Genre: Business & Economics
ISBN: 3662462141

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This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.

Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing

Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing
Author: Hime Aguiar e Oliveira Junior
Publisher: Springer Science & Business Media
Total Pages: 210
Release: 2012-01-26
Genre: Technology & Engineering
ISBN: 364227479X

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Stochastic global optimization is a very important subject, that has applications in virtually all areas of science and technology. Therefore there is nothing more opportune than writing a book about a successful and mature algorithm that turned out to be a good tool in solving difficult problems. Here we present some techniques for solving several problems by means of Fuzzy Adaptive Simulated Annealing (Fuzzy ASA), a fuzzy-controlled version of ASA, and by ASA itself. ASA is a sophisticated global optimization algorithm that is based upon ideas of the simulated annealing paradigm, coded in the C programming language and developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space. By presenting detailed examples of its application we want to stimulate the reader’s intuition and make the use of Fuzzy ASA (or regular ASA) easier for everyone wishing to use these tools to solve problems. We kept formal mathematical requirements to a minimum and focused on continuous problems, although ASA is able to handle discrete optimization tasks as well. This book can be used by researchers and practitioners in engineering and industry, in courses on optimization for advanced undergraduate and graduate levels, and also for self-study.

Global Optimization

Global Optimization
Author: Stefan Schäffler
Publisher: Springer Science & Business Media
Total Pages: 157
Release: 2012-06-26
Genre: Mathematics
ISBN: 1461439272

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This self-contained monograph presents a new stochastic approach to global optimization problems arising in a variety of disciplines including mathematics, operations research, engineering, and economics. The volume deals with constrained and unconstrained problems and puts a special emphasis on large scale problems. It also introduces a new unified concept for unconstrained, constrained, vector, and stochastic global optimization problems. All methods presented are illustrated by various examples. Practical numerical algorithms are given and analyzed in detail. The topics presented include the randomized curve of steepest descent, the randomized curve of dominated points, the semi-implicit Euler method, the penalty approach, and active set strategies. The optimal decoding of block codes in digital communications is worked out as a case study and shows the potential and high practical relevance of this new approach. Global Optimization: A Stochastic Approach is an elegant account of a refined theory, suitable for researchers and graduate students interested in global optimization and its applications.

Introduction to Stochastic Search and Optimization

Introduction to Stochastic Search and Optimization
Author: James C. Spall
Publisher: John Wiley & Sons
Total Pages: 620
Release: 2005-03-11
Genre: Mathematics
ISBN: 0471441902

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* 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.