Introduction to Global Optimization Exploiting Space Filling Curves

Author: Yaroslav D. Sergeyev
Publisher: Springer Science & Business Media
ISBN: 1461480426
Format: PDF, ePub, Docs
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Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, such as adaptive strategies for estimating Lipschitz constant, balancing global and local information to accelerate the search. Convergence conditions of the described algorithms are studied in depth and theoretical considerations are illustrated through numerical examples. This work also contains a code for implementing space-filling curves that can be used for constructing new global optimization algorithms. Basic ideas from this text can be applied to a number of problems including problems with multiextremal and partially defined constraints and non-redundant parallel computations can be organized. Professors, students, researchers, engineers, and other professionals in the fields of pure mathematics, nonlinear sciences studying fractals, operations research, management science, industrial and applied mathematics, computer science, engineering, economics, and the environmental sciences will find this title useful . ​

Simplicial Global Optimization

Author: Remigijus Paulavičius
Publisher: Springer Science & Business Media
ISBN: 1461490936
Format: PDF, Mobi
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Simplicial Global Optimization is centered on deterministic covering methods partitioning feasible region by simplices. This book looks into the advantages of simplicial partitioning in global optimization through applications where the search space may be significantly reduced while taking into account symmetries of the objective function by setting linear inequality constraints that are managed by initial partitioning. The authors provide an extensive experimental investigation and illustrates the impact of various bounds, types of subdivision, strategies of candidate selection on the performance of algorithms. A comparison of various Lipschitz bounds over simplices and an extension of Lipschitz global optimization with-out the Lipschitz constant to the case of simplicial partitioning is also depicted in this text. Applications benefiting from simplicial partitioning are examined in detail such as nonlinear least squares regression and pile placement optimization in grillage-type foundations. Researchers and engineers will benefit from simplicial partitioning algorithms such as Lipschitz branch and bound, Lipschitz optimization without the Lipschitz constant, heuristic partitioning presented. This book will leave readers inspired to develop simplicial versions of other algorithms for global optimization and even use other non-rectangular partitions for special applications.

Deterministic Global Optimization

Author: Yaroslav D. Sergeyev
Publisher: Springer
ISBN: 1493971999
Format: PDF, ePub, Docs
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This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed. Theoretical considerations are illustrated through engineering applications. Extensive numerical testing of algorithms described in this book stretches the likelihood of establishing a link between mathematicians and practitioners. The authors conclude by describing applications and a generator of random classes of test functions with known local and global minima that is used in more than 40 countries of the world. This title serves as a starting point for students, researchers, engineers, and other professionals in operations research, management science, computer science, engineering, economics, environmental sciences, industrial and applied mathematics to obtain an overview of deterministic global optimization.

Antenna Design by Simulation Driven Optimization

Author: Slawomir Koziel
Publisher: Springer Science & Business Media
ISBN: 3319043676
Format: PDF, Mobi
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This Brief reviews a number of techniques exploiting the surrogate-based optimization concept and variable-fidelity EM simulations for efficient optimization of antenna structures. The introduction of each method is illustrated with examples of antenna design. The authors demonstrate the ways in which practitioners can obtain an optimized antenna design at the computational cost corresponding to a few high-fidelity EM simulations of the antenna structure. There is also a discussion of the selection of antenna model fidelity and its influence on performance of the surrogate-based design process. This volume is suitable for electrical engineers in academia as well as industry, antenna designers and engineers dealing with computationally-expensive design problems.

Learning and Intelligent Optimization

Author: Roberto Battiti
Publisher: Springer
ISBN: 3319694049
Format: PDF, ePub, Docs
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This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Learning and Intelligent Optimization, LION 11, held in Nizhny,Novgorod, Russia, in June 2017. The 20 full papers (among these one GENOPT paper) and 15 short papers presented have been carefully reviewed and selected from 73 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.

Models Algorithms and Technologies for Network Analysis

Author: Valery A. Kalyagin
Publisher: Springer
ISBN: 3319568299
Format: PDF, Mobi
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This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and human brain networks are presented. Chapters in this book cover the following topics: Linear max min fairness Heuristic approaches for high-quality solutions Efficient approaches for complex multi-criteria optimization problems Comparison of heuristic algorithms New heuristic iterative local search Power in network structures Clustering nodes in random graphs Power transmission grid structure Network decomposition problems Homogeneity hypothesis testing Network analysis of international migration Social networks with node attributes Testing hypothesis on degree distribution in the market graphs Machine learning applications to human brain network studies This proceeding is a result of The 6th International Conference on Network Analysis held at the Higher School of Economics, Nizhny Novgorod in May 2016. The conference brought together scientists and engineers from industry, government, and academia to discuss the links between network analysis and a variety of fields.

Predator Prey Interactions Co evolution between Bats and Their Prey

Author: David Steve Jacobs
Publisher: Springer
ISBN: 3319324926
Format: PDF, ePub, Mobi
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This book provides a comprehensive review of the evolution of traits associated with predation and predator defense for bats and all of their prey, both invertebrates (e.g. insects) and vertebrates (e.g. frogs), in the context of co-evolution. It reviews current knowledge of how echolocation and passive hearing are used by bats to hunt prey in complete darkness. Also it highlights how prey have evolved counter measures to bat echolocation to avoid detection and capture. This includes the whole range of prey responses from being active at times when bats are inactive to the use of acoustic signals of their own to interfere with the echolocation system of bats.

Interactive Segmentation Techniques

Author: Jia He
Publisher: Springer Science & Business Media
ISBN: 9814451606
Format: PDF, ePub, Mobi
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This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided with quantitative and qualitative performance evaluation, which will be illustrated using natural and synthetic images. Also, extensive statistical performance comparisons will be made. Pros and cons of these interactive segmentation methods will be pointed out, and their applications will be discussed. There have been only a few surveys on interactive segmentation techniques, and those surveys do not cover recent state-of-the art techniques. By providing comprehensive up-to-date survey on the fast developing topic and the performance evaluation, this book can help readers learn interactive segmentation techniques quickly and thoroughly.

IBM PowerAI Deep Learning Unleashed on IBM Power Systems Servers

Author: Dino Quintero
Publisher: IBM Redbooks
ISBN: 0738442941
Format: PDF, Docs
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This IBM® Redbooks® publication is a guide about the IBM PowerAI Deep Learning solution. This book provides an introduction to artificial intelligence (AI) and deep learning (DL), IBM PowerAI, and components of IBM PowerAI, deploying IBM PowerAI, guidelines for working with data and creating models, an introduction to IBM SpectrumTM Conductor Deep Learning Impact (DLI), and case scenarios. IBM PowerAI started as a package of software distributions of many of the major DL software frameworks for model training, such as TensorFlow, Caffe, Torch, Theano, and the associated libraries, such as CUDA Deep Neural Network (cuDNN). The IBM PowerAI software is optimized for performance by using the IBM Power SystemsTM servers that are integrated with NVLink. The AI stack foundation starts with servers with accelerators. graphical processing unit (GPU) accelerators are well-suited for the compute-intensive nature of DL training, and servers with the highest CPU to GPU bandwidth, such as IBM Power Systems servers, enable the high-performance data transfer that is required for larger and more complex DL models. This publication targets technical readers, including developers, IT specialists, systems architects, brand specialist, sales team, and anyone looking for a guide about how to understand the IBM PowerAI Deep Learning architecture, framework configuration, application and workload configuration, and user infrastructure.

Global Optimization with Non Convex Constraints

Author: Roman G. Strongin
Publisher: Springer Science & Business Media
ISBN: 146154677X
Format: PDF, Docs
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Everything should be made as simple as possible, but not simpler. (Albert Einstein, Readers Digest, 1977) The modern practice of creating technical systems and technological processes of high effi.ciency besides the employment of new principles, new materials, new physical effects and other new solutions ( which is very traditional and plays the key role in the selection of the general structure of the object to be designed) also includes the choice of the best combination for the set of parameters (geometrical sizes, electrical and strength characteristics, etc.) concretizing this general structure, because the Variation of these parameters ( with the structure or linkage being already set defined) can essentially affect the objective performance indexes. The mathematical tools for choosing these best combinations are exactly what is this book about. With the advent of computers and the computer-aided design the pro bations of the selected variants are usually performed not for the real examples ( this may require some very expensive building of sample op tions and of the special installations to test them ), but by the analysis of the corresponding mathematical models. The sophistication of the mathematical models for the objects to be designed, which is the natu ral consequence of the raising complexity of these objects, greatly com plicates the objective performance analysis. Today, the main (and very often the only) available instrument for such an analysis is computer aided simulation of an object's behavior, based on numerical experiments with its mathematical model.