Experimental Methods For The Analysis Of Optimization Algorithms
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Experimental Methods For The Analysis Of Optimization Algorithms
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Author : Thomas Bartz-Beielstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-02
Experimental Methods For The Analysis Of Optimization Algorithms written by Thomas Bartz-Beielstein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-02 with Computers categories.
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.
Experimental Research In Evolutionary Computation
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Author : Thomas Bartz-Beielstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-09
Experimental Research In Evolutionary Computation written by Thomas Bartz-Beielstein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-09 with Computers categories.
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.
Analysis Of Experimental Algorithms
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Author : Ilias Kotsireas
language : en
Publisher: Springer Nature
Release Date : 2019-11-14
Analysis Of Experimental Algorithms written by Ilias Kotsireas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-14 with Computers categories.
This book constitutes the refereed post-conference proceedings of the Special Event on the Analysis of Experimental Algorithms, SEA2 2019, held in Kalamata, Greece, in June 2019. The 35 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers cover a wide range of topics in both computer science and operations research/mathematical programming. They focus on the role of experimentation and engineering techniques in the design and evaluation of algorithms, data structures, and computational optimization methods.
The Design And Analysis Of Computer Experiments
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Author : Thomas J. Santner
language : en
Publisher: Springer
Release Date : 2019-01-08
The Design And Analysis Of Computer Experiments written by Thomas J. Santner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-08 with Mathematics categories.
This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners
Multimodal Optimization By Means Of Evolutionary Algorithms
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Author : Mike Preuss
language : en
Publisher: Springer
Release Date : 2015-11-27
Multimodal Optimization By Means Of Evolutionary Algorithms written by Mike Preuss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-27 with Computers categories.
This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.
Experiments Planning Analysis And Parameter Design Optimization
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Author : C.F. Jeff Wu
language : en
Publisher:
Release Date : 2009-01-01
Experiments Planning Analysis And Parameter Design Optimization written by C.F. Jeff Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with categories.
Market_Desc: Masters- and PhD-level courses in departments of Statistics, Engineering, and Biostatistics; Industrial Users/Professionals who seek a sourcebook for industrial experimentation; Direct Mail Buyers or Trade Audience who seek an up-to-date reference volume on the subject-matter Special Features: · Written by award-winning authors. · Modernizes the accepted methodologies first introduced in written form in Statistics for Experimenters (0-471-09315-7). · Incorporates high-powered and user-friendly computing techniques such as graphical methods, generalized linear models, and Bayesian computing. · New data analysis strategies and algorithms for analyzing designed experiments based on these computing methods. · Features case studies featuring the goal of an investigation, the data, the experimental plan and their levels, as well as 17-18 data sets, chapter summarizes Bayesian analysis approaches, and self-contained mathematical derivations. · Includes new discoveries and material, among them robust parameter design, reliability improvement, analysis of non-normal data, an unusual and innovative approach to multi-level designs, analysis of experiments with complex analysis, and novel design techniques (such as orthogonal arrays) never seen before in-print. · A unique approach to the treatment of design tables. About The Book: 1. Author backgrounds are simply incredible: Wu is Chair at one of the top ten statistics institutions in the world, while Hamada is a hard-working, recognized industrialist (also at Michigan). 2. JWS needs a replacement to BHH; this volume could very well be that book. 3. The inclusion of modern, never-seen-before topics is compelling, at the very least as a complement to BHH. We would hate for any competitor to get this project.
Experimental Algorithms
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Author :
language : en
Publisher:
Release Date : 2008
Experimental Algorithms written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computer algorithms categories.
This book constitutes the refereed proceedings of the 7th International Workshop on Experimental and Efficient Algorithms, WEA 2008, held in Provincetown, MA, USA, in May/June 2008. The 26 revised full papers were carefully reviewed and selected from numerous submissions and present current research on experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications. Special focus is put on the use of experimental methods to guide the design, analysis, implementation, and evaluation of algorithms, heuristics, and optimization programs.
Uncertainty Management In Simulation Optimization Of Complex Systems
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Author : Gabriella Dellino
language : en
Publisher: Springer
Release Date : 2015-06-29
Uncertainty Management In Simulation Optimization Of Complex Systems written by Gabriella Dellino and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-29 with Business & Economics categories.
This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together — as chapter contributors — researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors’ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.
Black Box Optimization Machine Learning And No Free Lunch Theorems
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Author : Panos M. Pardalos
language : en
Publisher: Springer Nature
Release Date : 2021-05-27
Black Box Optimization Machine Learning And No Free Lunch Theorems written by Panos M. Pardalos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-27 with Mathematics categories.
This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems. Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.
Statistical And Computational Techniques In Manufacturing
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Author : J. Paulo Davim
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-06
Statistical And Computational Techniques In Manufacturing written by J. Paulo Davim and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-06 with Technology & Engineering categories.
In recent years, interest in developing statistical and computational techniques for applied manufacturing engineering has been increased. Today, due to the great complexity of manufacturing engineering and the high number of parameters used, conventional approaches are no longer sufficient. Therefore, in manufacturing, statistical and computational techniques have achieved several applications, namely, modelling and simulation manufacturing processes, optimization manufacturing parameters, monitoring and control, computer-aided process planning, etc. The present book aims to provide recent information on statistical and computational techniques applied in manufacturing engineering. The content is suitable for final undergraduate engineering courses or as a subject on manufacturing at the postgraduate level. This book serves as a useful reference for academics, statistical and computational science researchers, mechanical, manufacturing and industrial engineers, and professionals in industries related to manufacturing engineering.