Experimental Methods for the Analysis of Optimization Algorithms (Record no. 111419)

000 -LEADER
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001 - CONTROL NUMBER
control field 978-3-642-02538-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220084523.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642025389
-- 978-3-642-02538-9
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-02538-9
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYAM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code UFM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM077000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.55
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bartz-Beielstein, Thomas.
Relator term editor.
245 10 - TITLE STATEMENT
Title Experimental Methods for the Analysis of Optimization Algorithms
Medium [electronic resource] /
Statement of responsibility, etc edited by Thomas Bartz-Beielstein, Marco Chiarandini, Luís Paquete, Mike Preuss.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg,
-- 2010.
300 ## - PHYSICAL DESCRIPTION
Extent XXII, 457p. 93 illus.
Other physical details online resource.
336 ## -
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-- computer
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-- online resource
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-- text file
-- PDF
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Operations research.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Physics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Probability and Statistics in Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Operations Research, Mathematical Programming.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Complexity.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Chiarandini, Marco.
Relator term editor.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Paquete, Luís.
Relator term editor.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Preuss, Mike.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642025372
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-02538-9
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