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Optimization by the Pattern Search Method by Ralph F. Green Pdf
An infinite number of mathematical models can be created to describe naturally occurring physical systems. In addition there is a smaller, but large, number of criteria which can be used to measure the goodness of fit of a model to a physical process. Together, a selected criterion and a mathematical model define an objective function to be optimized.
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.
A Derivative-free Two Level Random Search Method for Unconstrained Optimization by Neculai Andrei Pdf
The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free optimization method/algorithm based on randomly generated trial points in specified domains and where the best ones are selected at each iteration by using a number of rules. This method is different from many other well established methods presented in the literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a relative large number of variables. Intensive numerical experiments with 140 unconstrained optimization problems, with up to 500 variables, have shown that this approach is efficient and robust. Structured into 4 chapters, Chapter 1 is introductory. Chapter 2 is dedicated to presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous, lower bounded and its minimum value is known. Chapter 3 proves the convergence of the algorithm. In Chapter 4, the numerical performances of the algorithm are shown for solving 140 unconstrained optimization problems, out of which 16 are real applications. This shows that the optimization process has two phases: the reduction phase and the stalling one. Finally, the performances of the algorithm for solving a number of 30 large-scale unconstrained optimization problems up to 500 variables are presented. These numerical results show that this approach based on the two level random search method for unconstrained optimization is able to solve a large diversity of problems with different structures and complexities. There are a number of open problems which refer to the following aspects: the selection of the number of trial or the number of the local trial points, the selection of the bounds of the domains where the trial points and the local trial points are randomly generated and a criterion for initiating the line search.
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.
OPTIMIZATION METHODS FOR ENGINEERS by N.V.S. Raju Pdf
Primarily designed as a text for the postgraduate students of mechanical engineering and related branches, it provides an excellent introduction to optimization methods—the overview, the history, and the development. It is equally suitable for the undergraduate students for their electives. The text then moves on to familiarize the students with the formulation of optimization problems, graphical solutions, analytical methods of nonlinear optimization, classical optimization techniques, single variable (one-dimensional) unconstrained optimization, multidimensional problems, constrained optimization, equality and inequality constraints. With complexities of human life, the importance of optimization techniques as a tool has increased manifold. The application of optimization techniques creates an efficient, effective and a better life. Features • Includes numerous illustrations and unsolved problems. • Contains university questions. • Discusses the topics with step-by-step procedures.
A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds by Robert Michael Lewis,Institute for Computer Applications in Science and Engineering,Virginia Torczon Pdf
Reactive Power Control in AC Power Systems by Naser Mahdavi Tabatabaei,Ali Jafari Aghbolaghi,Nicu Bizon,Frede Blaabjerg Pdf
This textbook explores reactive power control and voltage stability and explains how they relate to different forms of power generation and transmission. Bringing together international experts in this field, it includes chapters on electric power analysis, design and operational strategies. The book explains fundamental concepts before moving on to report on the latest theoretical findings in reactive power control, including case studies and advice on practical implementation students can use to design their own research projects. Featuring numerous worked-out examples, problems and solutions, as well as over 400 illustrations, Reactive Power Control in AC Power Systems offers an essential textbook for postgraduate students in electrical power engineering. It offers practical advice on implementing the methods discussed in the book using MATLAB and DIgSILENT, and the relevant program files are available at extras.springer.com.
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition by Serkan Kiranyaz,Turker Ince,Moncef Gabbouj Pdf
For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.
Smart Manufacturing Innovation and Transformation: Interconnection and Intelligence by Luo, ZongWei Pdf
Fast advances in information technology have led to a smarter world vision with ubiquitous interconnection and intelligence. Smart Manufacturing Innovation and Transformation: Interconnection and Intelligence covers both theoretical perspectives and practical approaches to smart manufacturing research and development triggered by ubiquitous interconnection and intelligence. This reference work discusses the transformation of manufacturing, the latest developments in smart manufacturing innovation, current and emerging technology opportunities, and market imperatives that enable manufacturing innovation and transformation, useful tools for readers in industry, academia, and government.
Manufacturing Optimization through Intelligent Techniques by Rajendran Saravanan Pdf
Effective utilization of equipment is critical to any manufacturing operation, especially with today's sophisticated, high-cost equipment and increased global competition. To meet these challenges in the manufacturing industry, you must understand and implement the myriad conventional and intelligent techniques for different types of manufacturing problems. Manufacturing Optimization Through Intelligent Techniques covers design of machine elements, integrated product development, machining tolerance allocation, selection of operating parameters for CNC machine tools, scheduling, part family formation, selection of robot coordinates, robot trajectory planning and both conventional and intelligent techniques, providing the tools to design and implement a suitable optimization technique. The author explores how to model optimization problems, select suitable techniques, develop the optimization algorithm and software, and implement the program. The book delineates five new techniques using examples taken from the literature for optimization problems in design, tolerance allocation; selection of machining parameters, integrated product development, scheduling, concurrent formation of machine groups and part families, selection of robot co-ordinates, robot trajectory planning and intelligent machining. All the manufacturing functions described have been successfully solved by Genetic Algorithm. Other intelligent techniques have been implemented only for solving certain types of problems: simulated annealing; design and scheduling, particle swarm optimization and ant colony optimization; tolerance allocation and tabu search; as well as machining parameters optimization. After reading this book, you will understand the different types of manufacturing optimization problems as well as the conventional and intelligent techniques suitable for solving them. You will also be able to develop and implement effective optimization procedures and algorithms for a wide variety of problems in design manufacturing.
Global Minimization of Nonconvex Energy Functions by Panos M. Pardalos,David Shalloway,Guoliang Xue Pdf
This book contains refereed papers presented at a remarkable interdisciplinary scientific meeting attended by a mix of leading biochemists and computer scientists held at DIMACS in March 1995. It describes the development of a variety og new methods which are being developed for attacking the important problem of molecular structure.
Optimization Based Clearance of Flight Control Laws by Andreas Varga,Anders Hansson,Guilhem Puyou Pdf
This book summarizes the main achievements of the EC funded 6th Framework Program project COFCLUO – Clearance of Flight Control Laws Using Optimization. This project successfully contributed to the achievement of a top-level objective to meet society’s needs for a more efficient, safer and environmentally friendly air transport by providing new techniques and tools for the clearance of flight control laws. This is an important part of the certification and qualification process of an aircraft – a costly and time-consuming process for the aeronautical industry. The overall objective of the COFCLUO project was to develop and apply optimization techniques to the clearance of flight control laws in order to improve efficiency and reliability. In the book, the new techniques are explained and benchmarked against traditional techniques currently used by the industry. The new techniques build on mathematical criteria derived from the certification and qualification requirements together with suitable models of the aircraft. The development of these criteria and models are also presented in the book. Because of wider applicability, the optimization-based clearance of flight control laws will open up the possibility to design innovative aircraft that today are out of the scope using classical clearance tools. Optimization-based clearance will not only increase safety but it will also simplify the whole certification and qualification process, thus significantly reduce cost. The achieved speedup will also support rapid modeling and prototyping and reduce “time to market”.
Solving Optimization Problems with MATLAB® by Dingyü Xue Pdf
This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed integer, multiobjective and dynamic programming problems. Comparative studies and conclusions on intelligent global solvers are also provided.
Numerical Optimization by Jorge Nocedal,Stephen Wright Pdf
Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Array Pattern Optimization by Jafar Ramadhan Mohammed,Khalil Sayidmarie Pdf
Array pattern optimization is a very important and necessary issue in the majority of modern communication systems in a variety of applications such as sonar, radar, navigation, wireless communications, and many other engineering fields. Classical methods for array pattern synthesis have worked mainly with analytical models that are linear, local and, thus, their performances were not optimum. They have always been designed with closed-form mathematical models. Unlike these analytical methods, the global optimization methods with powerful computing tools offer optimum solutions. During the last few years, the design of the antenna arrays has been a topic of significant research activity. This book presents recent advances in the field of array pattern optimization. It is targeted primarily toward students and researchers who want to be exposed to a wide variety of antenna array design and optimization. It includes five chapters as well as the introductory chapter. These five chapters are categorized into five different areas depending on the application. These applications are ordered to address interference suppression, electronic toll collection, mmWave and ultra-wideband, integrated antennas, and educational packages for modeling smart antenna for 5G wireless communications. The book has the advantage of providing a collection of applications that are entirely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity.