Experimental Methods for the Analysis of O...

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Beschreibung

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.

Zusammenfassung

First book to offer full treatment on this subject

Contributor include leading scientists in algorithm design, statistical design, optimization and heuristics

Most chapters provide theoretical background and are enriched with case studies

Includes supplementary material: [...]

Inhaltsverzeichnis

Overview.- The Future of Experimental Research.- Design and Analysis of Computational Experiments: Overview.- The Generation of Experimental Data for Computational Testing in Optimization.- The Attainment-Function Approach to Stochastic Multiobjective Optimizer Assessment and Comparison.- Algorithm Engineering: Concepts and Practice.- Characterizing Algorithm Performance.- Algorithm Survival Analysis.- On Applications of Extreme Value Theory in Optimization.- Exploratory Analysis of Stochastic Local Search Algorithms in Biobjective Optimization.- Algorithm Configuration and Tuning.- Mixed Models for the Analysis of Optimization Algorithms.- Tuning an Algorithm Using Design of Experiments.- Using Entropy for Parameter Analysis of Evolutionary Algorithms.- F-Race and Iterated F-Race: An Overview.- The Sequential Parameter Optimization Toolbox.- Sequential Model-Based Parameter Optimization: an Experimental Investigation of Automated and Interactive Approaches.

Erscheinungsjahr:	2010
Genre:	Informatik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Seiten:	480
Inhalt:	xxii 457 S.
ISBN-13:	9783642025372
ISBN-10:	3642025374
Sprache:	Englisch
Herstellernummer:	12539253
Ausstattung / Beilage:	HC runder Rücken kaschiert
Einband:	Gebunden
Redaktion:	Bartz-Beielstein, Thomas Preuss, Mike Paquete, Luís Chiarandini, Marco
Herausgeber:	Thomas Bartz-Beielstein/Marco Chiarandini/Luís Paquete et al
Auflage:	2010
Hersteller:	Springer Berlin Springer Berlin Heidelberg
Maße:	241 x 160 x 34 mm
Von/Mit:	Thomas Bartz-Beielstein (u. a.)
Erscheinungsdatum:	04.11.2010
Gewicht:	0,969 kg

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