Experimental Methods For The Analysis Of Optimization Algorithms

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Experimental Methods for the Analysis of Optimization Algorithms

Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss
Experimental Methods for the Analysis of Optimization Algorithms Book PDF

Author : Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss
Publisher : Springer Science & Business Media
Page : 469 pages
File Size : 52,9 Mb
Release : 2010-11-02
Category : Computers
ISBN : 9783642025389

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Experimental Methods for the Analysis of Optimization Algorithms by Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss Pdf

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.

Multimodal Optimization by Means of Evolutionary Algorithms

Mike Preuss
Multimodal Optimization by Means of Evolutionary Algorithms Book PDF

Author : Mike Preuss
Publisher : Springer
Page : 189 pages
File Size : 40,6 Mb
Release : 2015-11-27
Category : Computers
ISBN : 9783319074078

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Multimodal Optimization by Means of Evolutionary Algorithms by Mike Preuss Pdf

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.

Experimental Research in Evolutionary Computation

Thomas Bartz-Beielstein
Experimental Research in Evolutionary Computation Book PDF

Author : Thomas Bartz-Beielstein
Publisher : Springer Science & Business Media
Page : 215 pages
File Size : 48,6 Mb
Release : 2006-05-09
Category : Computers
ISBN : 9783540320272

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Experimental Research in Evolutionary Computation by Thomas Bartz-Beielstein Pdf

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.

Uncertainty Management in Simulation-Optimization of Complex Systems

Gabriella Dellino,Carlo Meloni
Uncertainty Management in Simulation Optimization of Complex Systems Book PDF

Author : Gabriella Dellino,Carlo Meloni
Publisher : Springer
Page : 271 pages
File Size : 49,9 Mb
Release : 2015-06-29
Category : Business & Economics
ISBN : 9781489975478

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Uncertainty Management in Simulation-Optimization of Complex Systems by Gabriella Dellino,Carlo Meloni Pdf

​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

Panos M. Pardalos,Varvara Rasskazova,Michael N. Vrahatis
Black Box Optimization Machine Learning and No Free Lunch Theorems Book PDF

Author : Panos M. Pardalos,Varvara Rasskazova,Michael N. Vrahatis
Publisher : Springer Nature
Page : 388 pages
File Size : 44,8 Mb
Release : 2021-05-27
Category : Mathematics
ISBN : 9783030665159

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Black Box Optimization, Machine Learning, and No-Free Lunch Theorems by Panos M. Pardalos,Varvara Rasskazova,Michael N. Vrahatis Pdf

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.

Analysis of Experimental Algorithms

Ilias Kotsireas,Panos Pardalos,Konstantinos E. Parsopoulos,Dimitris Souravlias,Arsenis Tsokas
Analysis of Experimental Algorithms Book PDF

Author : Ilias Kotsireas,Panos Pardalos,Konstantinos E. Parsopoulos,Dimitris Souravlias,Arsenis Tsokas
Publisher : Springer Nature
Page : 564 pages
File Size : 51,7 Mb
Release : 2019-11-14
Category : Computers
ISBN : 9783030340292

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Analysis of Experimental Algorithms by Ilias Kotsireas,Panos Pardalos,Konstantinos E. Parsopoulos,Dimitris Souravlias,Arsenis Tsokas Pdf

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.

Experimental Algorithms

Catherine C. McGeoch
Experimental Algorithms Book PDF

Author : Catherine C. McGeoch
Publisher : Springer Science & Business Media
Page : 371 pages
File Size : 48,5 Mb
Release : 2008-05-08
Category : Computers
ISBN : 9783540685487

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Experimental Algorithms by Catherine C. McGeoch Pdf

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.

Statistical and Computational Techniques in Manufacturing

J. Paulo Davim
Statistical and Computational Techniques in Manufacturing Book PDF

Author : J. Paulo Davim
Publisher : Springer Science & Business Media
Page : 285 pages
File Size : 51,9 Mb
Release : 2012-03-06
Category : Technology & Engineering
ISBN : 9783642258596

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Statistical and Computational Techniques in Manufacturing by J. Paulo Davim Pdf

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.

Learning and Intelligent Optimization

Giuseppe Nicosia,Panos Pardalos
Learning and Intelligent Optimization Book PDF

Author : Giuseppe Nicosia,Panos Pardalos
Publisher : Springer
Page : 470 pages
File Size : 42,5 Mb
Release : 2013-11-26
Category : Computers
ISBN : 9783642449734

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Learning and Intelligent Optimization by Giuseppe Nicosia,Panos Pardalos Pdf

This book constitutes the proceedings of the 7th International Conference on Learning and Optimization, LION 7, which was held in Catania, Italy, in January 2013. The 49 contributions presented in this volume were carefully reviewed and selected from 101 submissions. They explore the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems.

A Guide to Experimental Algorithmics

Catherine C. McGeoch
A Guide to Experimental Algorithmics Book PDF

Author : Catherine C. McGeoch
Publisher : Cambridge University Press
Page : 273 pages
File Size : 49,8 Mb
Release : 2012-01-30
Category : Computers
ISBN : 9781107001732

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A Guide to Experimental Algorithmics by Catherine C. McGeoch Pdf

This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.

Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications

Carrillo-Cedillo, Eugenia Gabriela,Rodríguez-Avila, José Antonio,Arredondo-Soto, Karina Cecilia,Cornejo-Bravo, José Manuel
Design of Experiments for Chemical Pharmaceutical Food and Industrial Applications Book PDF

Author : Carrillo-Cedillo, Eugenia Gabriela,Rodríguez-Avila, José Antonio,Arredondo-Soto, Karina Cecilia,Cornejo-Bravo, José Manuel
Publisher : IGI Global
Page : 429 pages
File Size : 54,9 Mb
Release : 2019-12-13
Category : Science
ISBN : 9781799815204

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Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications by Carrillo-Cedillo, Eugenia Gabriela,Rodríguez-Avila, José Antonio,Arredondo-Soto, Karina Cecilia,Cornejo-Bravo, José Manuel Pdf

Statistics is a key characteristic that assists a wide variety of professions including business, government, and factual sciences. Companies need data calculation to make informed decisions that help maintain their relevance. Design of experiments (DOE) is a set of active techniques that provides a more efficient approach for industries to test their processes and form effective conclusions. Experimental design can be implemented into multiple professions, and it is a necessity to promote applicable research on this up-and-coming method. Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications is a pivotal reference source that seeks to increase the use of design of experiments to optimize and improve analytical methods and productive processes in order to use less resources and time. While highlighting topics such as multivariate methods, factorial experiments, and pharmaceutical research, this publication is ideally designed for industrial designers, research scientists, chemical engineers, managers, academicians, and students seeking current research on advanced and multivariate statistics.

Metaheuristics for Dynamic Optimization

Enrique Alba,Amir Nakib,Patrick Siarry
Metaheuristics for Dynamic Optimization Book PDF

Author : Enrique Alba,Amir Nakib,Patrick Siarry
Publisher : Springer
Page : 400 pages
File Size : 51,7 Mb
Release : 2012-08-11
Category : Technology & Engineering
ISBN : 9783642306655

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Metaheuristics for Dynamic Optimization by Enrique Alba,Amir Nakib,Patrick Siarry Pdf

This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.

Springer Handbook of Computational Intelligence

Janusz Kacprzyk,Witold Pedrycz
Springer Handbook of Computational Intelligence Book PDF

Author : Janusz Kacprzyk,Witold Pedrycz
Publisher : Springer
Page : 1634 pages
File Size : 55,8 Mb
Release : 2015-05-28
Category : Technology & Engineering
ISBN : 9783662435052

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Springer Handbook of Computational Intelligence by Janusz Kacprzyk,Witold Pedrycz Pdf

The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Learning and Intelligent Optimization

Panos M. Pardalos,Mauricio G.C. Resende,Chrysafis Vogiatzis,Jose L. Walteros
Learning and Intelligent Optimization Book PDF

Author : Panos M. Pardalos,Mauricio G.C. Resende,Chrysafis Vogiatzis,Jose L. Walteros
Publisher : Springer
Page : 392 pages
File Size : 47,6 Mb
Release : 2014-07-31
Category : Computers
ISBN : 9783319095844

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Learning and Intelligent Optimization by Panos M. Pardalos,Mauricio G.C. Resende,Chrysafis Vogiatzis,Jose L. Walteros Pdf

This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Learning and Optimization, LION 8, which was held in Gainesville, FL, USA, in February 2014. The 33 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as algorithm configuration; multiobjective optimization; metaheuristics; graphs and networks; logistics and transportation; and biomedical applications.

Proceedings. 20. Workshop Computational Intelligence, Dortmund, 1. Dezember - 3. Dezember 2010

Frank Hoffmann,E. Hüllermeier
Proceedings 20 Workshop Computational Intelligence Dortmund 1 Dezember 3 Dezember 2010 Book PDF

Author : Frank Hoffmann,E. Hüllermeier
Publisher : KIT Scientific Publishing
Page : 328 pages
File Size : 53,5 Mb
Release : 2014-08-14
Category : Computers
ISBN : 9783866445802

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Proceedings. 20. Workshop Computational Intelligence, Dortmund, 1. Dezember - 3. Dezember 2010 by Frank Hoffmann,E. Hüllermeier Pdf

Dieser Tagungsband enthält die Beiträge des 20. Workshops "Computational Intelligence" des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) der vom 1.-3. Dezember 2010 im Haus Bommerholz (Dortmund) stattfand. Die Schwerpunkte waren Methoden, Anwendungen und Tools für- Fuzzy-Systeme, - Künstliche Neuronale Netze, - Evolutionäre Algorithmen und- Data-Mining-Verfahrensowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen.