Numerical Infinities and Infinitesimals in Optimization

Numerical Infinities and Infinitesimals in Optimization

Author: Yaroslav D. Sergeyev

Publisher: Springer Nature

Published: 2022-07-05

Total Pages: 372

ISBN-13: 3030936422

DOWNLOAD EBOOK

This book provides a friendly introduction to the paradigm and proposes a broad panorama of killing applications of the Infinity Computer in optimization: radically new numerical algorithms, great theoretical insights, efficient software implementations, and interesting practical case studies. This is the first book presenting to the readers interested in optimization the advantages of a recently introduced supercomputing paradigm that allows to numerically work with different infinities and infinitesimals on the Infinity Computer patented in several countries. One of the editors of the book is the creator of the Infinity Computer, and another editor was the first who has started to use it in optimization. Their results were awarded by numerous scientific prizes. This engaging book opens new horizons for researchers, engineers, professors, and students with interests in supercomputing paradigms, optimization, decision making, game theory, and foundations of mathematics and computer science. “Mathematicians have never been comfortable handling infinities... But an entirely new type of mathematics looks set to by-pass the problem... Today, Yaroslav Sergeyev, a mathematician at the University of Calabria in Italy solves this problem... ” MIT Technology Review “These ideas and future hardware prototypes may be productive in all fields of science where infinite and infinitesimal numbers (derivatives, integrals, series, fractals) are used.” A. Adamatzky, Editor-in-Chief of the International Journal of Unconventional Computing. “I am sure that the new approach ... will have a very deep impact both on Mathematics and Computer Science.” D. Trigiante, Computational Management Science. “Within the grossone framework, it becomes feasible to deal computationally with infinite quantities, in a way that is both new (in the sense that previously intractable problems become amenable to computation) and natural”. R. Gangle, G. Caterina, F. Tohmé, Soft Computing. “The computational features offered by the Infinity Computer allow us to dynamically change the accuracy of representation and floating-point operations during the flow of a computation. When suitably implemented, this possibility turns out to be particularly advantageous when solving ill-conditioned problems. In fact, compared with a standard multi-precision arithmetic, here the accuracy is improved only when needed, thus not affecting that much the overall computational effort.” P. Amodio, L. Brugnano, F. Iavernaro & F. Mazzia, Soft Computing


Numerical Infinities and Infinitesimals in Optimization

Numerical Infinities and Infinitesimals in Optimization

Author: Yaroslav D. Sergeyev

Publisher:

Published: 2022

Total Pages: 0

ISBN-13: 9788303093646

DOWNLOAD EBOOK

This book provides a friendly introduction to the paradigm and proposes a broad panorama of killing applications of the Infinity Computer in optimization: radically new numerical algorithms, great theoretical insights, efficient software implementations, and interesting practical case studies. This is the first book presenting to the readers interested in optimization the advantages of a recently introduced supercomputing paradigm that allows to numerically work with different infinities and infinitesimals on the Infinity Computer patented in several countries. One of the editors of the book is the creator of the Infinity Computer, and another editor was the first who has started to use it in optimization. Their results were awarded by numerous scientific prizes. This engaging book opens new horizons for researchers, engineers, professors, and students with interests in supercomputing paradigms, optimization, decision making, game theory, and foundations of mathematics and computer science.


Mathematical Optimization Theory and Operations Research

Mathematical Optimization Theory and Operations Research

Author: Michael Khachay

Publisher: Springer Nature

Published: 2023-06-25

Total Pages: 459

ISBN-13: 3031353056

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 22nd International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2023, held in Ekaterinburg, Russia, during July 2–8, 2023. The 28 full papers and 1 short paper included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: Mathematical programming and applications; discrete and combinatorial optimization; stochastic optimization; scheduling; game theory; and optimal control and mathematical economics. The book also contains one invited talk in full paper length.


Mathematical Optimization Theory and Operations Research

Mathematical Optimization Theory and Operations Research

Author: Panos Pardalos

Publisher: Springer Nature

Published: 2022-06-24

Total Pages: 332

ISBN-13: 303109607X

DOWNLOAD EBOOK

This book constitutes the proceedings of the 21st International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2022, held in Petrozavodsk, Russia, in July 2022. The 21 full papers presented together with 6 invited abstracts lectures and 2 tutorial abstracts in this volume were carefully reviewed and selected from 88 submissions. The conference focuses on the following topics: Mathematical programming, bi-level and global optimization, integer programming and combinatorial optimization, approximation algorithms with theoretical guarantees and approximation schemes, heuristics and meta-heuristics, game theory, optimal control, optimization in machine learning and data analysis, and their valuable applications in operations research and economics.


Learning and Intelligent Optimization

Learning and Intelligent Optimization

Author: Dimitris E. Simos

Publisher: Springer Nature

Published: 2023-02-04

Total Pages: 576

ISBN-13: 303124866X

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 16th International Conference on Learning and Intelligent Optimization, LION 16, which took place in Milos Island, Greece, in June 2022. The 36 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 60 submissions. LION deals with automatic solver configuration, parallel methods, intelligent optimization, nature-inspired algorithms, hard combinatorial optimization problems, DC learning, computational intelligence, and others. The contributions were organized in topical sections as follows: Invited Papers; Contributed Papers.


Numerical Computations: Theory and Algorithms

Numerical Computations: Theory and Algorithms

Author: Yaroslav D. Sergeyev

Publisher: Springer Nature

Published: 2020-02-13

Total Pages: 550

ISBN-13: 3030406164

DOWNLOAD EBOOK

The two-volume set LNCS 11973 and 11974 constitute revised selected papers from the Third International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2019, held in Crotone, Italy, in June 2019. This volume, LNCS 11974, consists of 19 full and 32 short papers chosen among regular papers presented at the the Conference including also the paper of the winner (Lorenzo Fiaschi, Pisa, Italy) of The Springer Young Researcher Prize for the best NUMTA 2019 presentation made by a young scientist. The papers in part II explore the advanced research developments in such interconnected fields as local and global optimization, machine learning, approximation, and differential equations. A special focus is given to advanced ideas related to methods and applications using emerging computational paradigms.


Learning and Intelligent Optimization

Learning and Intelligent Optimization

Author: Roberto Battiti

Publisher: Springer

Published: 2018-12-31

Total Pages: 487

ISBN-13: 3030053482

DOWNLOAD EBOOK

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Learning and Intelligent Optimization, LION 12, held in Kalamata, Greece, in June 2018. The 28 full papers and 12 short papers presented have been carefully reviewed and selected from 62 submissions. The papers explore the advanced research developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning.


Numerical Optimization

Numerical Optimization

Author: Jorge Nocedal

Publisher: Springer Science & Business Media

Published: 2006-06-06

Total Pages: 651

ISBN-13: 0387227423

DOWNLOAD EBOOK

The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on methods best suited to practical problems. This edition has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are widely used in practice and are the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience.


Large-scale Numerical Optimization

Large-scale Numerical Optimization

Author: Thomas Frederick Coleman

Publisher: SIAM

Published: 1990-01-01

Total Pages: 278

ISBN-13: 9780898712681

DOWNLOAD EBOOK

Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.


Bayesian and High-Dimensional Global Optimization

Bayesian and High-Dimensional Global Optimization

Author: Anatoly Zhigljavsky

Publisher: Springer Nature

Published: 2021-03-02

Total Pages: 125

ISBN-13: 3030647129

DOWNLOAD EBOOK

Accessible to a variety of readers, this book is of interest to specialists, graduate students and researchers in mathematics, optimization, computer science, operations research, management science, engineering and other applied areas interested in solving optimization problems. Basic principles, potential and boundaries of applicability of stochastic global optimization techniques are examined in this book. A variety of issues that face specialists in global optimization are explored, such as multidimensional spaces which are frequently ignored by researchers. The importance of precise interpretation of the mathematical results in assessments of optimization methods is demonstrated through examples of convergence in probability of random search. Methodological issues concerning construction and applicability of stochastic global optimization methods are discussed, including the one-step optimal average improvement method based on a statistical model of the objective function. A significant portion of this book is devoted to an analysis of high-dimensional global optimization problems and the so-called ‘curse of dimensionality’. An examination of the three different classes of high-dimensional optimization problems, the geometry of high-dimensional balls and cubes, very slow convergence of global random search algorithms in large-dimensional problems , and poor uniformity of the uniformly distributed sequences of points are included in this book.