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Experimental Methods for the Analysis of Optimization Algorithms

Experimental Methods for the Analysis of Optimization Algorithms by Thomas Bartz-Beielstein
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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.

Springer Berlin Heidelberg; November 2010
469 pages; ISBN 9783642025389
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Title: Experimental Methods for the Analysis of Optimization Algorithms
Author: Thomas Bartz-Beielstein; Marco Chiarandini; Luís Paquete; Mike Preuss
 
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ISBNs
3642025382
9783642025372
9783642025389