Open Problems In Optimization And Data Analysis
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| Author | : Panos M. Pardalos |
| Publisher | : Springer |
| Total Pages | : 341 |
| Release | : 2018-12-04 |
| Genre | : Mathematics |
| ISBN | : 3319991426 |
Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.
| Author | : Stephen J. Wright |
| Publisher | : Cambridge University Press |
| Total Pages | : 239 |
| Release | : 2022-04-21 |
| Genre | : Computers |
| ISBN | : 1316518981 |
A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.
| Author | : M. R. Osborne |
| Publisher | : |
| Total Pages | : 408 |
| Release | : 1985-12-23 |
| Genre | : Mathematics |
| ISBN | : |
The significance and originality of this book derive from its novel approach to those optimization problems in which an active set strategy leads to a finite algorithm, such as linear and quadratic programming or l1 and l approximations.
| Author | : Boris Goldengorin |
| Publisher | : Springer |
| Total Pages | : 516 |
| Release | : 2016-09-29 |
| Genre | : Mathematics |
| ISBN | : 3319420569 |
This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015. This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.
| Author | : Anton Eremeev |
| Publisher | : Springer |
| Total Pages | : 351 |
| Release | : 2018-06-29 |
| Genre | : Computers |
| ISBN | : 3319938002 |
This book constitutes extended, revised and selected papers from the 7th International Conference on Optimization Problems and Their Applications, OPTA 2018, held in Omsk, Russia in July 2018. The 27 papers presented in this volume were carefully reviewed and selected from a total of 73 submissions. The papers are listed in thematic sections, namely location problems, scheduling and routing problems, optimization problems in data analysis, mathematical programming, game theory and economical applications, applied optimization problems and metaheuristics.
| Author | : Ali Emrouznejad |
| Publisher | : Springer |
| Total Pages | : 492 |
| Release | : 2016-05-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3319302655 |
The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.
| Author | : Miroslav Fiedler |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 222 |
| Release | : 2006-07-18 |
| Genre | : Mathematics |
| ISBN | : 0387326987 |
Linear programming has attracted the interest of mathematicians since World War II when the first computers were constructed. Early attempts to apply linear programming methods practical problems failed, in part because of the inexactness of the data used to create the models. This book presents a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.
| Author | : Dimitris Souravlias |
| Publisher | : Springer Nature |
| Total Pages | : 92 |
| Release | : 2021-03-24 |
| Genre | : Business & Economics |
| ISBN | : 3030685144 |
This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.
| Author | : Panos M. Pardalos |
| Publisher | : Springer |
| Total Pages | : 469 |
| Release | : 2011-04-21 |
| Genre | : Computers |
| ISBN | : 364220662X |
This volume constitutes the refereed proceedings of the 10th International Symposium on Experimental Algorithms, SEA 2011, held in Kolimpari, Chania, Crete, Greece, in May 2011. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions and present current research in the area of design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications.
| Author | : J.Frederic Bonnans |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 618 |
| Release | : 2013-11-22 |
| Genre | : Mathematics |
| ISBN | : 1461213940 |
A presentation of general results for discussing local optimality and computation of the expansion of value function and approximate solution of optimization problems, followed by their application to various fields, from physics to economics. The book is thus an opportunity for popularizing these techniques among researchers involved in other sciences, including users of optimization in a wide sense, in mechanics, physics, statistics, finance and economics. Of use to research professionals, including graduate students at an advanced level.
