Computational Optimization Methods and Algorithms

Computational Optimization  Methods and Algorithms
Author: Slawomir Koziel,Xin-She Yang
Publsiher: Springer
Total Pages: 283
Release: 2011-06-17
ISBN 10: 3642208592
ISBN 13: 9783642208591
Language: EN, FR, DE, ES & NL

Computational Optimization Methods and Algorithms Book Review:

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 and Applications in Engineering and Industry

Computational Optimization and Applications in Engineering and Industry
Author: Xin-She Yang,Slawomir Koziel
Publsiher: Springer Science & Business Media
Total Pages: 282
Release: 2011-06-19
ISBN 10: 3642209858
ISBN 13: 9783642209857
Language: EN, FR, DE, ES & NL

Computational Optimization and Applications in Engineering and Industry Book Review:

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.

Computational Combinatorial Optimization

Computational Combinatorial Optimization
Author: Michael Jünger,Denis Naddef
Publsiher: Springer
Total Pages: 310
Release: 2003-06-30
ISBN 10: 3540455868
ISBN 13: 9783540455868
Language: EN, FR, DE, ES & NL

Computational Combinatorial Optimization Book Review:

This tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.

Computational Optimization

Computational Optimization
Author: Jong-Shi Pang
Publsiher: Springer Science & Business Media
Total Pages: 273
Release: 2012-12-06
ISBN 10: 1461551978
ISBN 13: 9781461551973
Language: EN, FR, DE, ES & NL

Computational Optimization Book Review:

Computational Optimization: A Tribute to Olvi Mangasarian serves as an excellent reference, providing insight into some of the most challenging research issues in the field. This collection of papers covers a wide spectrum of computational optimization topics, representing a blend of familiar nonlinear programming topics and such novel paradigms as semidefinite programming and complementarity-constrained nonlinear programs. Many new results are presented in these papers which are bound to inspire further research and generate new avenues for applications. An informal categorization of the papers includes: Algorithmic advances for special classes of constrained optimization problems Analysis of linear and nonlinear programs Algorithmic advances B- stationary points of mathematical programs with equilibrium constraints Applications of optimization Some mathematical topics Systems of nonlinear equations.

Computational Optimization Techniques and Applications

Computational Optimization Techniques and Applications
Author: Muhammad Sarfraz,Samsul Ariffin Abdul Karim
Publsiher: BoD – Books on Demand
Total Pages: 245
Release: 2021-08-25
ISBN 10: 1839687657
ISBN 13: 9781839687655
Language: EN, FR, DE, ES & NL

Computational Optimization Techniques and Applications Book Review:

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.

Recent Advances in Computational Optimization

Recent Advances in Computational Optimization
Author: Stefka Fidanova
Publsiher: Springer
Total Pages: 244
Release: 2015-07-14
ISBN 10: 3319211331
ISBN 13: 9783319211336
Language: EN, FR, DE, ES & NL

Recent Advances in Computational Optimization Book Review:

This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2014, held at Warsaw, Poland, September 7-10, 2014. The book presents recent advances in computational optimization. The volume includes important real problems like parameter settings for controlling processes in bioreactor and other processes, resource constrained project scheduling, infection distribution, molecule distance geometry, quantum computing, real-time management and optimal control, bin packing, medical image processing, localization the abrupt atmospheric contamination source and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.

Computational Optimization of Internal Combustion Engines

Computational Optimization of Internal Combustion Engines
Author: Yu Shi,Hai-Wen Ge,Rolf D. Reitz
Publsiher: Springer Science & Business Media
Total Pages: 309
Release: 2011-06-22
ISBN 10: 0857296191
ISBN 13: 9780857296191
Language: EN, FR, DE, ES & NL

Computational Optimization of Internal Combustion Engines Book Review:

Computational Optimization of Internal Combustion Engines presents the state of the art of computational models and optimization methods for internal combustion engine development using multi-dimensional computational fluid dynamics (CFD) tools and genetic algorithms. Strategies to reduce computational cost and mesh dependency are discussed, as well as regression analysis methods. Several case studies are presented in a section devoted to applications, including assessments of: spark-ignition engines, dual-fuel engines, heavy duty and light duty diesel engines. Through regression analysis, optimization results are used to explain complex interactions between engine design parameters, such as nozzle design, injection timing, swirl, exhaust gas recirculation, bore size, and piston bowl shape. Computational Optimization of Internal Combustion Engines demonstrates that the current multi-dimensional CFD tools are mature enough for practical development of internal combustion engines. It is written for researchers and designers in mechanical engineering and the automotive industry.

Intelligent Computational Optimization in Engineering

Intelligent Computational Optimization in Engineering
Author: Mario Koeppen,Gerald Schaefer,Ajith Abraham
Publsiher: Springer Science & Business Media
Total Pages: 400
Release: 2011-07-15
ISBN 10: 3642217044
ISBN 13: 9783642217043
Language: EN, FR, DE, ES & NL

Intelligent Computational Optimization in Engineering Book Review:

We often come across computational optimization virtually in all branches of engineering and industry. Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice. Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications.This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry.

Computational Optimization in Engineering

Computational Optimization in Engineering
Author: Hossein Peyvandi
Publsiher: BoD – Books on Demand
Total Pages: 164
Release: 2017-04-26
ISBN 10: 9535130811
ISBN 13: 9789535130819
Language: EN, FR, DE, ES & NL

Computational Optimization in Engineering Book Review:

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.

Optimization in Computational Chemistry and Molecular Biology

Optimization in Computational Chemistry and Molecular Biology
Author: Christodoulos A. Floudas,Panos M. Pardalos
Publsiher: Springer Science & Business Media
Total Pages: 342
Release: 2000-02-29
ISBN 10: 9780792361558
ISBN 13: 0792361555
Language: EN, FR, DE, ES & NL

Optimization in Computational Chemistry and Molecular Biology Book Review:

Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches covers recent developments in optimization techniques for addressing several computational chemistry and biology problems. A tantalizing problem that cuts across the fields of computational chemistry, biology, medicine, engineering and applied mathematics is how proteins fold. Global and local optimization provide a systematic framework of conformational searches for the prediction of three-dimensional protein structures that represent the global minimum free energy, as well as low-energy biomolecular conformations. Each contribution in the book is essentially expository in nature, but of scholarly treatment. The topics covered include advances in local and global optimization approaches for molecular dynamics and modeling, distance geometry, protein folding, molecular structure refinement, protein and drug design, and molecular and peptide docking. Audience: The book is addressed not only to researchers in mathematical programming, but to all scientists in various disciplines who use optimization methods in solving problems in computational chemistry and biology.

Handbook of Machine Learning for Computational Optimization

Handbook of Machine Learning for Computational Optimization
Author: Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan
Publsiher: CRC Press
Total Pages: 294
Release: 2021-11-02
ISBN 10: 100045567X
ISBN 13: 9781000455670
Language: EN, FR, DE, ES & NL

Handbook of Machine Learning for Computational Optimization Book Review:

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Introduction to Computational Optimization Models for Production Planning in a Supply Chain

Introduction to Computational Optimization Models for Production Planning in a Supply Chain
Author: Stefan Voß,David L. Woodruff
Publsiher: Springer Science & Business Media
Total Pages: 233
Release: 2013-06-05
ISBN 10: 3540247645
ISBN 13: 9783540247647
Language: EN, FR, DE, ES & NL

Introduction to Computational Optimization Models for Production Planning in a Supply Chain Book Review:

An easy-to-read introduction to the concepts associated with the creation of optimization models for production planning starts off this book. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, fairly sophisticated models for supply chain management are developed. Another unique feature is that models are developed with an eye toward implementation. In fact, there is a chapter that provides explicit examples of implementation of the basic models using a variety of popular, commercially available modeling languages.

Optimization and Computational Fluid Dynamics

Optimization and Computational Fluid Dynamics
Author: Dominique Thévenin,Gábor Janiga
Publsiher: Springer Science & Business Media
Total Pages: 294
Release: 2008-01-08
ISBN 10: 3540721533
ISBN 13: 9783540721536
Language: EN, FR, DE, ES & NL

Optimization and Computational Fluid Dynamics Book Review:

The numerical optimization of practical applications has been an issue of major importance for the last 10 years. It allows us to explore reliable non-trivial configurations, differing widely from all known solutions. The purpose of this book is to introduce the state-of-the-art concerning this issue and many complementary applications are presented.

Numerical Optimization with Computational Errors

Numerical Optimization with Computational Errors
Author: Alexander J. Zaslavski
Publsiher: Springer
Total Pages: 304
Release: 2016-04-22
ISBN 10: 3319309218
ISBN 13: 9783319309217
Language: EN, FR, DE, ES & NL

Numerical Optimization with Computational Errors Book Review:

This book studies the approximate solutions of optimization problems in the presence of computational errors. A number of results are presented on the convergence behavior of algorithms in a Hilbert space; these algorithms are examined taking into account computational errors. The author illustrates that algorithms generate a good approximate solution, if computational errors are bounded from above by a small positive constant. Known computational errors are examined with the aim of determining an approximate solution. Researchers and students interested in the optimization theory and its applications will find this book instructive and informative. This monograph contains 16 chapters; including a chapters devoted to the subgradient projection algorithm, the mirror descent algorithm, gradient projection algorithm, the Weiszfelds method, constrained convex minimization problems, the convergence of a proximal point method in a Hilbert space, the continuous subgradient method, penalty methods and Newton’s method.

Advances in Computational and Stochastic Optimization Logic Programming and Heuristic Search

Advances in Computational and Stochastic Optimization  Logic Programming  and Heuristic Search
Author: David L. Woodruff
Publsiher: Springer Science & Business Media
Total Pages: 312
Release: 1997-12-31
ISBN 10: 9780792380788
ISBN 13: 0792380789
Language: EN, FR, DE, ES & NL

Advances in Computational and Stochastic Optimization Logic Programming and Heuristic Search Book Review:

Computer Science and Operations Research continue to have a synergistic relationship and this book - as a part of the Operations Research and Computer Science Interface Series - sits squarely in the center of the confluence of these two technical research communities. The research presented in the volume is evidence of the expanding frontiers of these two intersecting disciplines and provides researchers and practitioners with new work in the areas of logic programming, stochastic optimization, heuristic search and post-solution analysis for integer programs. The chapter topics span the spectrum of application level. Some of the chapters are highly applied and others represent work in which the application potential is only beginning. In addition, each chapter contains expository material and reviews of the literature designed to enhance the participation of the reader in this expanding interface.

Convex Optimization with Computational Errors

Convex Optimization with Computational Errors
Author: Alexander J. Zaslavski
Publsiher: Springer Nature
Total Pages: 360
Release: 2020-01-31
ISBN 10: 3030378225
ISBN 13: 9783030378226
Language: EN, FR, DE, ES & NL

Convex Optimization with Computational Errors Book Review:

The book is devoted to the study of approximate solutions of optimization problems in the presence of computational errors. It contains a number of results on the convergence behavior of algorithms in a Hilbert space, which are known as important tools for solving optimization problems. The research presented in the book is the continuation and the further development of the author's (c) 2016 book Numerical Optimization with Computational Errors, Springer 2016. Both books study the algorithms taking into account computational errors which are always present in practice. The main goal is, for a known computational error, to find out what an approximate solution can be obtained and how many iterates one needs for this. The main difference between this new book and the 2016 book is that in this present book the discussion takes into consideration the fact that for every algorithm, its iteration consists of several steps and that computational errors for different steps are generally, different. This fact, which was not taken into account in the previous book, is indeed important in practice. For example, the subgradient projection algorithm consists of two steps. The first step is a calculation of a subgradient of the objective function while in the second one we calculate a projection on the feasible set. In each of these two steps there is a computational error and these two computational errors are different in general. It may happen that the feasible set is simple and the objective function is complicated. As a result, the computational error, made when one calculates the projection, is essentially smaller than the computational error of the calculation of the subgradient. Clearly, an opposite case is possible too. Another feature of this book is a study of a number of important algorithms which appeared recently in the literature and which are not discussed in the previous book. This monograph contains 12 chapters. Chapter 1 is an introduction. In Chapter 2 we study the subgradient projection algorithm for minimization of convex and nonsmooth functions. We generalize the results of [NOCE] and establish results which has no prototype in [NOCE]. In Chapter 3 we analyze the mirror descent algorithm for minimization of convex and nonsmooth functions, under the presence of computational errors. For this algorithm each iteration consists of two steps. The first step is a calculation of a subgradient of the objective function while in the second one we solve an auxiliary minimization problem on the set of feasible points. In each of these two steps there is a computational error. We generalize the results of [NOCE] and establish results which has no prototype in [NOCE]. In Chapter 4 we analyze the projected gradient algorithm with a smooth objective function under the presence of computational errors. In Chapter 5 we consider an algorithm, which is an extension of the projection gradient algorithm used for solving linear inverse problems arising in signal/image processing. In Chapter 6 we study continuous subgradient method and continuous subgradient projection algorithm for minimization of convex nonsmooth functions and for computing the saddle points of convex-concave functions, under the presence of computational errors. All the results of this chapter has no prototype in [NOCE]. In Chapters 7-12 we analyze several algorithms under the presence of computational errors which were not considered in [NOCE]. Again, each step of an iteration has a computational errors and we take into account that these errors are, in general, different. An optimization problems with a composite objective function is studied in Chapter 7. A zero-sum game with two-players is considered in Chapter 8. A predicted decrease approximation-based method is used in Chapter 9 for constrained convex optimization. Chapter 10 is devoted to minimization of quasiconvex functions. Minimization of sharp weakly convex functions is discussed in Chapter 11. Chapter 12 is devoted to a generalized projected subgradient method for minimization of a convex function over a set which is not necessarily convex. The book is of interest for researchers and engineers working in optimization. It also can be useful in preparation courses for graduate students. The main feature of the book which appeals specifically to this audience is the study of the influence of computational errors for several important optimization algorithms. The book is of interest for experts in applications of optimization to engineering and economics.

Computational Methods in Optimization

Computational Methods in Optimization
Author: E. Polak
Publsiher: Academic Press
Total Pages: 329
Release: 1971-05-31
ISBN 10: 9780080960913
ISBN 13: 008096091X
Language: EN, FR, DE, ES & NL

Computational Methods in Optimization Book Review:

Computational Methods in Optimization

Bioinspired Computation in Combinatorial Optimization

Bioinspired Computation in Combinatorial Optimization
Author: Frank Neumann,Carsten Witt
Publsiher: Springer Science & Business Media
Total Pages: 216
Release: 2010-11-04
ISBN 10: 3642165443
ISBN 13: 9783642165443
Language: EN, FR, DE, ES & NL

Bioinspired Computation in Combinatorial Optimization Book Review:

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.

Recent Advances in Computational Optimization

Recent Advances in Computational Optimization
Author: Stefka Fidanova
Publsiher: Springer Nature
Total Pages: 490
Release: 2021-12-14
ISBN 10: 3030823970
ISBN 13: 9783030823979
Language: EN, FR, DE, ES & NL

Recent Advances in Computational Optimization Book Review:

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 and Regularization for Computational Inverse Problems and Applications

Optimization and Regularization for Computational Inverse Problems and Applications
Author: Yanfei Wang,Anatoly G. Yagola,Changchun Yang
Publsiher: Springer Science & Business Media
Total Pages: 400
Release: 2011-06-29
ISBN 10: 3642137423
ISBN 13: 9783642137426
Language: EN, FR, DE, ES & NL

Optimization and Regularization for Computational Inverse Problems and Applications Book Review:

"Optimization and Regularization for Computational Inverse Problems and Applications" focuses on advances in inversion theory and recent developments with practical applications, particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated regularization, nonstandard regularization, nonlinear gradient method, the nonmonotone gradient method, subspace method and Lie group method; and the practical applications, such as the reconstruction problem for inverse scattering, molecular spectra data processing, quantitative remote sensing inversion, seismic inversion using the Lie group method, and the gravitational lensing problem. Scientists, researchers and engineers, as well as graduate students engaged in applied mathematics, engineering, geophysics, medical science, image processing, remote sensing and atmospheric science will benefit from this book. Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China. Dr. Sc. Anatoly G. Yagola is a Professor and Assistant Dean of the Physical Faculty, Lomonosov Moscow State University, Russia. Dr. Changchun Yang is a Professor and Vice Director of the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.