Articles by "Optimization"

Showing posts with label Optimization. Show all posts

George I. N. Rozvany,‎ Tomasz Lewinski ... 471 pages - Publisher: Springer; 1st edition (April, 2014) ... Language: English - ISBN-10: 3709116988 - ISBN-13: 978-3709116982 ...

The book covers new developments in structural topology optimization. Basic features and limitations of Michell’s truss theory, its extension to a broader class of support conditions, generalizations of truss topology optimization, and Michell continua are reviewed. For elastic bodies, the layout problems in linear elasticity are discussed and the method of relaxation by homogenization is outlined. The classical problem of free material design is shown to be reducible to a locking material problem, even in the multiload case. For structures subjected to dynamic loads, it is explained how they can be designed so that the structural eigenfrequencies of vibration are as far away as possible from a prescribed external excitation frequency (or a band of excitation frequencies) in order to avoid resonance phenomena with high vibration and noise levels. For diffusive and convective transport processes and multiphysics problems, applications of the density method are discussed. In order to take uncertainty in material parameters, geometry, and operating conditions into account, techniques of reliability-based design optimization are introduced and reviewed for their applicability to topology optimization.

Giuseppe C. Calafiore,‎ Laurent El Ghaoui ... 650 pages - Publisher: Cambridge Univ. Press; 1st edition (October, 2014) ... Language: English ... ISBN-10: 1107050871 - ISBN-13: 978-1107050877 ...

Emphasizing practical understanding over the technicalities of specific algorithms, this elegant textbook is an accessible introduction to the field of optimization, focusing on powerful and reliable convex optimization techniques. Students and practitioners will learn how to recognize, simplify, model and solve optimization problems - and apply these principles to their own projects. A clear and self-contained introduction to linear algebra demonstrates core mathematical concepts in a way that is easy to follow, and helps students to understand their practical relevance. Requiring only a basic understanding of geometry, calculus, probability and statistics, and striking a careful balance between accessibility and rigor, it enables students to quickly understand the material, without being overwhelmed by complex mathematics. Accompanied by numerous end-of-chapter problems, an online solutions manual for instructors, and relevant examples from diverse fields including engineering, data science, economics, finance, and management, this is the perfect introduction to optimization for undergraduate and graduate students.

Particle swarm optimization (PSO) is a population-based stochastic approach for solving continuous and discrete optimization problems. In particle swarm optimization, simple software agents, called particles, move in the search space of an optimization problem. The position of a particle represents a candidate solution to the optimization problem at hand. Each particle searches for better positions in the search space by changing its velocity according to rules originally inspired by behavioral models of bird flocking. Particle swarm optimization belongs to the class of swarm intelligence techniques that are used to solve optimization problems.

Jasbir S. Arora ... 610 pages - Publisher: Wspc; (September, 2007) ... Language: English - ASIN: B00O6AKF28 by Amazon Digital Services ...

Computational optimization methods have matured over the last few years due to extensive research by applied mathematicians and engineers. These methods have been applied to many practical applications. Several general-purpose optimization programs and programs for specific engineering applications have become available to solve particular optimization problems. Written by leading researchers in the field of optimization, this highly readable book covers state-of-the-art computational algorithms as well as applications of optimization to structural and mechanical systems. Formulations of the problems and numerical solutions are presented, and topics requiring further research are also suggested.

Stephen Satchell ... 328 pages - Publisher: Academic Press; 1st edition (October, 2009) ... Language: English - ISBN-10: 0750633611 - ISBN-13: 978-0750633611 ...

The practical aspects of optimization rarely receive global, balanced examinations. Stephen Satchell’s nuanced assembly of technical presentations about optimization packages (by their developers) and about current optimization practice and theory (by academic researchers) makes available highly practical solutions to our post-liquidity bubble environment. The commercial chapters emphasize algorithmic elements without becoming sales pitches, and the academic chapters create context and explore development opportunities. Together they offer an incisive perspective that stretches toward new products, new techniques, and new answers in quantitative finance. Presents a unique "confrontation" between software engineers and academics: * Highlights a global view of common optimization issues. * Emphasizes the research and market challenges of optimization software while avoiding sales pitches. * Accentuates real applications, not laboratory results.

Xin-She Yang ... 330 pages - Publisher: Springer; 1st edition (October, 2017) ... Language: English - ISBN-10: 3319676687 - ISBN-13: 978-3319676685 ...

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Syouji Nakamura, Toshio Nakagawa ... 316 pages - Publisher: World Scientific Publishing Company (November, 2009) ... Language: English - ISBN-10: 9814277436 - ISBN-13: 978-9814277433 ...

Reliability theory and applications become major concerns of engineers and managers engaged in making high quality products and designing highly reliable systems. This book aims to survey new research topics in reliability theory and useful applied techniques in reliability engineering. Our research group in Nagoya, Japan has continued to study reliability theory and applications for more than twenty years, and has presented and published many good papers at international conferences and in journals. This book focuses mainly on how to apply the results of reliability theory to practical models. Theoretical results of coherent, inspection, and damage systems are summarized methodically, using the techniques of stochastic processes. There exist optimization problems in computer and management sciences and engineering. It is shown that such problems as computer, information and network systems are solved by using the techniques of reliability. Furthermore, some useful techniques applied to the analysis of stochastic models in management science and plants are shown. The reader will learn new topics and techniques, and how to apply reliability models to actual ones. The book will serve as an essential guide to a subject of study for graduate students and researchers and as a useful guide for reliability engineers engaged not only in maintenance work but also in management and computer works.

Bradley P. Carlin, Thomas A. Louis ... 552 pages - Publisher: Chapman and Hall/CRC; 3rd edition (June, 2008) ... Language: English - ISBN-10: 1584886978 - ISBN-13: 978-1584886976 ...

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition: New data examples, corresponding R and WinBUGS code, and homework problems - Explicit descriptions and illustrations of hierarchical modeling―now commonplace in Bayesian data analysis - A new chapter on Bayesian design that emphasizes Bayesian clinical trials - A completely revised and expanded section on ranking and histogram estimation - A new case study on infectious disease modeling and the 1918 flu epidemic - A solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem―available both electronically and in print. Ideal for Anyone Performing Statistical Analyses: Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.

Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov ... 488 pages - Publisher: Springer; (September, 2014) ... Language: English - ISBN-10: 3319099027 - ISBN-13: 978-3319099026 ...

The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.

Stefan Schäffler ... 148 pages - Publisher: Springer; (June, 2012) ... Language: English - ASIN: B00A9YGPN8 by Amazon Digital Services ...

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.

Karl Hinderer, Ulrich Rieder, Michael Stieglitz ... 530 pages - Publisher: Springer; 1st edition (January, 2017) ... Language: English - ISBN-10: 3319488139 - ISBN-13: 978-3319488134 ...

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

W. T. Ziemba ... 756 pages - Publisher: World Scientific Publishing Company; (September, 2006) ... Language: English - ISBN-10: 981256800X - ISBN-13: 978-9812568007 ...

A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.

Paul Attewell, David Monaghan ... 264 pages - Publisher: Univ. of California Press; (May, 2015) ... Language: English - ISBN-10: 0520280989 - ISBN-13: 978-0520280984 ...

We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.

James R. Evans, Edward Minieka ... 488 pages - Publisher: CRC Press; 2nd edition (March, 1992) ... Language: English - ISBN-10: 0824786025 - ISBN-13: 978-0824786021 ...

A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm.

Shuming Wang, Junzo Watada ... 248 pages - Publisher: Springer; (March, 2012) ... Language: English - ISBN-10: 1441995595 - ISBN-13: 978-1441995599 ...

Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins by outlining the history and development of the fuzzy random variable before detailing numerous optimization models and applications that include the design of system controls for a dam.

Dimitri P. Bertsekas ... 608 pages - Publisher: Athena Scientific; (May, 1998) ... Language: English - ISBN-10: 1886529027 - ISBN-13: 978-1886529021 ...

An insightful, comprehensive, and up-to-date treatment of linear, nonlinear, and discrete/combinatorial network optimization problems, their applications, and their analytical and algorithmic methodology. It covers extensively theory, algorithms, and applications, and it aims to bridge the gap between linear and nonlinear network optimization on one hand, and integer/combinatorial network optimization on the other. Among its special features, the book: 1) provides a comprehensive account of the principal algorithms for linear network flow problems, including simplex, dual ascent, and auction algorithms 2) describes the application of network algorithms in many practical contexts, with special emphasis on data communication networks 3) develops in detail the computational complexity analysis of the main linear network optimization algorithms 4) covers extensively the main algorithms for specialized network problems, such as shortest path, max-flow, assignment, and traveling salesman 5) describes the main models for discrete network optimization problems, such as constrained shortest path, traveling salesman, vehicle routing, multidimensional assignment, facility location, spanning tree construction, etc 6) describes the main algorithmic approaches for integer-constrained network problems, such as branch-and-bound, Lagrangian relaxation and subgradient optimization, genetic algorithms, tabu search, simulated annealing, and rollout algorithms 7) develops the main methods for nonlinear network problems, such as convex separable and multicommodity flow problems arising in communication, transportation, and manufacturing contexts 8) discusses extensively auction algorithms, based on the author's original research on the subject 9) contains many examples, practical applications, illustrations, and exercises 10) contains much new material not found in any other textbook

Mitsuo Gen, Runwei Cheng, Lin Lin ... 692 pages - Publisher: Springer; (September, 2008) ... Language: English - ISBN-10: 1848001800 - ISBN-13: 978-1848001800 ...

Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

William Kocay, Donald L. Kreher ... 566 pages - Publisher: Chapman and Hall/CRC; 2nd edition (September, 2016) ... Language: English - ISBN-10: 1482251167 - ISBN-13: 978-1482251166 ...

The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.

Phil Kim ... 151 pages - Publisher: Apress; (June, 2017) ... Language: English - ISBN-10: 1484228448 - ISBN-13: 978-1484228449.

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage.

What You'll Learn: Use MATLAB for deep learning * Discover neural networks and multi-layer neural networks * Work with convolution and pooling layers * Build a MNIST example with these layers. Who This Book Is For: Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

Oliver Nelles ... 785 pages - Publisher: Springer; (December, 2000) ... Language: English - ISBN-10: 3540673695 - ISBN-13: 978-3540673699 ...

Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

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