Modern Optimization With R
Download Modern Optimization With R full books in PDF, epub, and Kindle. Read online free Modern Optimization With R ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads.
Author |
: Paulo Cortez |
Publisher |
: Springer |
Total Pages |
: 188 |
Release |
: 2014-09-22 |
ISBN-10 |
: 3319082620 |
ISBN-13 |
: 9783319082622 |
Rating |
: 4/5 (20 Downloads) |
Synopsis Modern Optimization with R by : Paulo Cortez
The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts 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.
Author |
: Paulo Cortez |
Publisher |
: Springer Nature |
Total Pages |
: 264 |
Release |
: 2021-07-30 |
ISBN-10 |
: 9783030728199 |
ISBN-13 |
: 3030728196 |
Rating |
: 4/5 (99 Downloads) |
Synopsis Modern Optimization with R by : Paulo Cortez
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).
Author |
: G. R. Sinha |
Publisher |
: |
Total Pages |
: 0 |
Release |
: 2019 |
ISBN-10 |
: 075032404X |
ISBN-13 |
: 9780750324045 |
Rating |
: 4/5 (4X Downloads) |
Synopsis Modern Optimization Methods for Science, Engineering and Technology by : G. R. Sinha
Achieving a better solution or improving the performance of existing system design is an ongoing a process for which scientists, engineers, mathematicians and researchers have been striving for many years. Ever increasingly practical and robust methods have been developed, and every new generation of computers with their increased power and speed allows for the development and wider application of new types of solutions. This book defines the fundamentals, background and theoretical concepts of optimization principles in a comprehensive manner along with their potential applications and implementation strategies. It encompasses linear programming, multivariable methods for risk assessment, nonlinear methods, ant colony optimization, particle swarm optimization, multi-criterion and topology optimization, learning classifier, case studies on six sigma, performance measures and evaluation, multi-objective optimization problems, machine learning approaches, genetic algorithms and quality of service optimizations. The book will be very useful for wide spectrum of target readers including students and researchers in academia and industry.
Author |
: Guillaume Carlier |
Publisher |
: World Scientific |
Total Pages |
: 388 |
Release |
: 2022-03-16 |
ISBN-10 |
: 9781800610675 |
ISBN-13 |
: 180061067X |
Rating |
: 4/5 (75 Downloads) |
Synopsis Classical And Modern Optimization by : Guillaume Carlier
The quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains active today, particularly in the development of machine learning.Classical and Modern Optimization presents a self-contained overview of classical and modern ideas and methods in approaching optimization problems. The approach is rich and flexible enough to address smooth and non-smooth, convex and non-convex, finite or infinite-dimensional, static or dynamic situations. The first chapters of the book are devoted to the classical toolbox: topology and functional analysis, differential calculus, convex analysis and necessary conditions for differentiable constrained optimization. The remaining chapters are dedicated to more specialized topics and applications.Valuable to a wide audience, including students in mathematics, engineers, data scientists or economists, Classical and Modern Optimization contains more than 200 exercises to assist with self-study or for anyone teaching a third- or fourth-year optimization class.
Author |
: Bernd Scherer |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 422 |
Release |
: 2007-09-05 |
ISBN-10 |
: 9780387275864 |
ISBN-13 |
: 038727586X |
Rating |
: 4/5 (64 Downloads) |
Synopsis Modern Portfolio Optimization with NuOPTTM, S-PLUS®, and S+BayesTM by : Bernd Scherer
In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.
Author |
: Giuseppe C. Calafiore |
Publisher |
: Cambridge University Press |
Total Pages |
: 651 |
Release |
: 2014-10-31 |
ISBN-10 |
: 9781107050877 |
ISBN-13 |
: 1107050871 |
Rating |
: 4/5 (77 Downloads) |
Synopsis Optimization Models by : Giuseppe C. Calafiore
This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.
Author |
: Aharon Ben-Tal |
Publisher |
: SIAM |
Total Pages |
: 500 |
Release |
: 2001-01-01 |
ISBN-10 |
: 9780898714913 |
ISBN-13 |
: 0898714915 |
Rating |
: 4/5 (13 Downloads) |
Synopsis Lectures on Modern Convex Optimization by : Aharon Ben-Tal
Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.
Author |
: Gerard Cornuejols |
Publisher |
: Cambridge University Press |
Total Pages |
: 358 |
Release |
: 2006-12-21 |
ISBN-10 |
: 0521861705 |
ISBN-13 |
: 9780521861700 |
Rating |
: 4/5 (05 Downloads) |
Synopsis Optimization Methods in Finance by : Gerard Cornuejols
Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.
Author |
: Dimitris Bertsimas |
Publisher |
: |
Total Pages |
: 589 |
Release |
: 2019 |
ISBN-10 |
: 1733788506 |
ISBN-13 |
: 9781733788502 |
Rating |
: 4/5 (06 Downloads) |
Synopsis Machine Learning Under a Modern Optimization Lens by : Dimitris Bertsimas
Author |
: Roberto Cominetti |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 265 |
Release |
: 2012-08-28 |
ISBN-10 |
: 9783034802918 |
ISBN-13 |
: 3034802919 |
Rating |
: 4/5 (18 Downloads) |
Synopsis Modern Optimization Modelling Techniques by : Roberto Cominetti
The theory of optimization, understood in a broad sense, is the basis of modern applied mathematics, covering a large spectrum of topics from theoretical considerations (structure, stability) to applied operational research and engineering applications. The compiled material of this book puts on display this versatility, by exhibiting the three parallel and complementary components of optimization: theory, algorithms, and practical problems. The book contains an expanded version of three series of lectures delivered by the authors at the CRM in July 2009. The first part is a self-contained course on the general moment problem and its relations with semidefinite programming. The second part is dedicated to the problem of determination of Nash equilibria from an algorithmic viewpoint. The last part presents congestion models for traffic networks and develops modern optimization techniques for finding traffic equilibria based on stochastic optimization and game theory.