INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
9783642025372
NATIONAL BIBLIOGRAPHY NUMBER
Country Code
IR
Number
EN-53843
LANGUAGE OF THE ITEM
.Language of Text, Soundtrack etc
انگلیسی
COUNTRY OF PUBLICATION OR PRODUCTlON
Country of publication
IR
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Experimental Methods for the Analysis of Optimization Algorithm
General Material Designation
[Book]
First Statement of Responsibility
/ [electronic resource
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
New York
Name of Publisher, Distributor, etc.
: Springer
Date of Publication, Distribution, etc.
, Nov. 2010.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xxii, 457 p., 23.500 015.500 cm.
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Electronic
CONTENTS NOTE
Text of Note
AnnotationIn 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.
SERIES
Title
SpringerLink ebooks - Computer Science (2010)
TOPICAL NAME USED AS SUBJECT
Electronic books
Mathematical Optimization
Computer Algorithms
Mathematics, Optimization
Computers, Programming, Algorithms
LIBRARY OF CONGRESS CLASSIFICATION
Class number
E-BOOK
PERSONAL NAME - PRIMARY RESPONSIBILITY
Bartz-Beielstein, ThomasEditor 4edt.
PERSONAL NAME - SECONDARY RESPONSIBILITY
Chiarandini, MarcoEditoredt
Paquete, Lu?sEditoredt
Preu?, MikeEditoredt
ORIGINATING SOURCE
Country
ایران
ELECTRONIC LOCATION AND ACCESS
Host name
9783642025372.pdf
Access number
عادی
Compression information
عادی
Date and Hour of Consultation and Access
9783642025372.pdf
Electronic Format Type
متن
old catalog
e
BL
1
a
Y
