Computational Optimization Methods And Algorithms

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Computational Optimization, Methods and Algorithms

Slawomir Koziel,Xin-She Yang
Computational Optimization Methods and Algorithms Book PDF

Author : Slawomir Koziel,Xin-She Yang
Publisher : Springer
Page : 292 pages
File Size : 40,8 Mb
Release : 2011-06-17
Category : Technology & Engineering
ISBN : 9783642208591

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Computational Optimization, Methods and Algorithms by Slawomir Koziel,Xin-She Yang Pdf

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 Techniques and Applications

Muhammad Sarfraz,Samsul Ariffin Abdul Karim
Computational Optimization Techniques and Applications Book PDF

Author : Muhammad Sarfraz,Samsul Ariffin Abdul Karim
Publisher : BoD – Books on Demand
Page : 245 pages
File Size : 42,7 Mb
Release : 2021-08-25
Category : Mathematics
ISBN : 9781839687655

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Computational Optimization Techniques and Applications by Muhammad Sarfraz,Samsul Ariffin Abdul Karim Pdf

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.

Intelligent Computational Optimization in Engineering

Mario Köppen,Gerald Schaefer,Ajith Abraham
Intelligent Computational Optimization in Engineering Book PDF

Author : Mario Köppen,Gerald Schaefer,Ajith Abraham
Publisher : Springer
Page : 400 pages
File Size : 50,8 Mb
Release : 2011-07-15
Category : Technology & Engineering
ISBN : 9783642217050

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Intelligent Computational Optimization in Engineering by Mario Köppen,Gerald Schaefer,Ajith Abraham Pdf

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.

Feasibility and Infeasibility in Optimization:

John W. Chinneck
Feasibility and Infeasibility in Optimization Book PDF

Author : John W. Chinneck
Publisher : Springer Science & Business Media
Page : 274 pages
File Size : 50,9 Mb
Release : 2007-10-25
Category : Mathematics
ISBN : 9780387749327

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Feasibility and Infeasibility in Optimization: by John W. Chinneck Pdf

Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.

Computational Optimization and Applications in Engineering and Industry

Xin-She Yang,Slawomir Koziel
Computational Optimization and Applications in Engineering and Industry Book PDF

Author : Xin-She Yang,Slawomir Koziel
Publisher : Springer Science & Business Media
Page : 282 pages
File Size : 51,9 Mb
Release : 2011-06-19
Category : Computers
ISBN : 9783642209857

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Computational Optimization and Applications in Engineering and Industry by Xin-She Yang,Slawomir Koziel Pdf

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.

Search and Optimization by Metaheuristics

Ke-Lin Du,M. N. S. Swamy
Search and Optimization by Metaheuristics Book PDF

Author : Ke-Lin Du,M. N. S. Swamy
Publisher : Birkhäuser
Page : 434 pages
File Size : 55,6 Mb
Release : 2016-07-20
Category : Computers
ISBN : 9783319411927

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Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy Pdf

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Recent Advances in Computational Optimization

Stefka Fidanova
Recent Advances in Computational Optimization Book PDF

Author : Stefka Fidanova
Publisher : Springer
Page : 236 pages
File Size : 42,6 Mb
Release : 2018-09-18
Category : Technology & Engineering
ISBN : 9783319996486

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Recent Advances in Computational Optimization by Stefka Fidanova Pdf

Our everyday lives are practically unthinkable without optimization. We constantly try to minimize our effort and to maximize the reward or progress achieved. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume presents a comprehensive collection of extended contributions from the 2017 Workshop on Computational Optimization. Presenting recent advances in computational optimization, it addresses important concrete applications, e.g. the modeling of physical processes, wildfire modeling, modeling processes in chemical engineering, workforce planning, wireless access network topology, parameter settings for controlling various processes, berth allocation, identification of homogeneous domains, and quantum computing. The book shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others.

Algorithms for Optimization

Mykel J. Kochenderfer,Tim A. Wheeler
Algorithms for Optimization Book PDF

Author : Mykel J. Kochenderfer,Tim A. Wheeler
Publisher : MIT Press
Page : 521 pages
File Size : 41,7 Mb
Release : 2019-03-12
Category : Computers
ISBN : 9780262039420

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Algorithms for Optimization by Mykel J. Kochenderfer,Tim A. Wheeler Pdf

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.

Optimization Methods in Operations Research and Systems Analysis

K V Mital
Optimization Methods in Operations Research and Systems Analysis Book PDF

Author : K V Mital
Publisher : New Age International
Page : 408 pages
File Size : 42,7 Mb
Release : 1996
Category : Linear programming
ISBN : 8122408737

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Optimization Methods in Operations Research and Systems Analysis by K V Mital Pdf

The Mathematical Aspects Of Operations Research And Systems Analysis Concerned With Optimization Of Objectives Form The Subject Of This Book. In Its Revised, Updated And Enlarged Third Edition, Discussion On Linear Programming Has Been Expanded And Recast With Greater Emphasis On Duality Theory, Sensitivity Analysis, Parametric Programming, Multiobjective And Goal Programming And Formulation And Solution Of Practical Problems. Chapters On Nonlinear Programming Include Integer Programming, Kuhn-Tucker Theory, Separable And Quadratic Programming, Dynamic Programming, Geometric Programming And Direct Search And Gradient Methods. A Chapter On Theory Of Games Is Also Included. A Short Note On Karmarkars Projective Algorithm Is Given In The Appendix.The Book Keeps In View The Needs Of The Student Taking A Regular Course In Operations Research Or Mathematical Programming, And Also Of Research Scholars In Other Disciplines Who Have A Limited Objective Of Learning The Practical Aspects Of Various Optimization Methods To Solve Their Special Problems. For The Former, Illustrative Solved Examples And Unsolved Examples At The End Of Each Chapter, Small Enough To Be Solved By Hand, Would Be Of Greater Interest, While For He Latter, Summaries Of Computational Algorithms For Various Methods Which Would Help Him To Write Computer Programmes To Solve Larger Problems Would Be More Helpful. A Few Computer Programmes In Fortran Iv Have Also Been Given In The Appendix.

Introduction to Optimization Methods

P. Adby
Introduction to Optimization Methods Book PDF

Author : P. Adby
Publisher : Springer Science & Business Media
Page : 214 pages
File Size : 51,5 Mb
Release : 2013-03-09
Category : Science
ISBN : 9789400957053

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Introduction to Optimization Methods by P. Adby Pdf

During the last decade the techniques of non-linear optim ization have emerged as an important subject for study and research. The increasingly widespread application of optim ization has been stimulated by the availability of digital computers, and the necessity of using them in the investigation of large systems. This book is an introduction to non-linear methods of optimization and is suitable for undergraduate and post graduate courses in mathematics, the physical and social sciences, and engineering. The first half of the book covers the basic optimization techniques including linear search methods, steepest descent, least squares, and the Newton-Raphson method. These are described in detail, with worked numerical examples, since they form the basis from which advanced methods are derived. Since 1965 advanced methods of unconstrained and constrained optimization have been developed to utilise the computational power of the digital computer. The second half of the book describes fully important algorithms in current use such as variable metric methods for unconstrained problems and penalty function methods for constrained problems. Recent work, much of which has not yet been widely applied, is reviewed and compared with currently popular techniques under a few generic main headings. vi PREFACE Chapter I describes the optimization problem in mathemat ical form and defines the terminology used in the remainder of the book. Chapter 2 is concerned with single variable optimization. The main algorithms of both search and approximation methods are developed in detail since they are an essential part of many multi-variable methods.

Optimization Algorithms

Ozgur Baskan
Optimization Algorithms Book PDF

Author : Ozgur Baskan
Publisher : BoD – Books on Demand
Page : 326 pages
File Size : 40,5 Mb
Release : 2016-09-21
Category : Mathematics
ISBN : 9789535125921

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Optimization Algorithms by Ozgur Baskan Pdf

This book covers state-of-the-art optimization methods and their applications in wide range especially for researchers and practitioners who wish to improve their knowledge in this field. It consists of 13 chapters divided into two parts: (I) Engineering applications, which presents some new applications of different methods, and (II) Applications in various areas, where recent contributions of state-of-the-art optimization methods to diverse fields are presented.

Recent Advances in Computational Optimization

Stefka Fidanova
Recent Advances in Computational Optimization Book PDF

Author : Stefka Fidanova
Publisher : Springer Nature
Page : 487 pages
File Size : 40,6 Mb
Release : 2021-12-14
Category : Technology & Engineering
ISBN : 9783030823979

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Recent Advances in Computational Optimization by Stefka Fidanova Pdf

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 Methods and Applications

Sergiy Butenko,Panos M. Pardalos,Volodymyr Shylo
Optimization Methods and Applications Book PDF

Author : Sergiy Butenko,Panos M. Pardalos,Volodymyr Shylo
Publisher : Springer
Page : 639 pages
File Size : 40,8 Mb
Release : 2018-02-20
Category : Mathematics
ISBN : 9783319686400

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Optimization Methods and Applications by Sergiy Butenko,Panos M. Pardalos,Volodymyr Shylo Pdf

Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization. Contributions from experts in optimization are showcased in this book showcase a broad range of applications and topics detailed in this volume, including pattern and image recognition, computer vision, robust network design, and process control in nonlinear distributed systems. This book is dedicated to the 80th birthday of Ivan V. Sergienko, who is a member of the National Academy of Sciences (NAS) of Ukraine and the director of the V.M. Glushkov Institute of Cybernetics. His work has had a significant impact on several theoretical and applied aspects of discrete optimization, computational mathematics, systems analysis and mathematical modeling.

Computational Intelligence for Optimization

Nirwan Ansari,Edwin Hou
Computational Intelligence for Optimization Book PDF

Author : Nirwan Ansari,Edwin Hou
Publisher : Springer Science & Business Media
Page : 228 pages
File Size : 54,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461563310

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Computational Intelligence for Optimization by Nirwan Ansari,Edwin Hou Pdf

The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.

Modern Optimization with R

Paulo Cortez
Modern Optimization with R Book PDF

Author : Paulo Cortez
Publisher : Springer Nature
Page : 264 pages
File Size : 53,6 Mb
Release : 2021-07-30
Category : Computers
ISBN : 9783030728199

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Modern Optimization with R by Paulo Cortez Pdf

The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed. These methods often yield high quality solutions with a more reasonable use of computational resources (e.g. memory and processing effort). Examples of popular modern methods discussed in this book are: simulated annealing; tabu search; genetic algorithms; differential evolution; and particle swarm optimization. This book is suitable for undergraduate and graduate students in computer science, information technology, and related areas, as well as data analysts interested in exploring modern optimization methods using R. This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution).