Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics (Record no. 184404)

MARC details
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001 - CONTROL NUMBER
control field 978-3-642-03751-1
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control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130036.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 100301s2009 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642037511
-- 978-3-642-03751-1
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-03751-1
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.6-76.66
072 #7 - SUBJECT CATEGORY CODE
Subject category code UM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM051000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UM
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.11
Edition number 23
245 10 - TITLE STATEMENT
Title Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Medium [electronic resource] :
Remainder of title International Workshop, SLS 2009, Brussels, Belgium, September 3-5, 2009, Proceedings /
Statement of responsibility, etc edited by Thomas Stützle, Mauro Birattari, Holger H. Hoos.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2009.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2009.
300 ## - PHYSICAL DESCRIPTION
Extent X, 155 p.
Other physical details online resource.
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-- computer
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Theoretical Computer Science and General Issues,
International Standard Serial Number 2512-2029 ;
Volume number/sequential designation 5752
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note High-Performance Local Search for Task Scheduling with Human Resource Allocation -- High-Performance Local Search for Task Scheduling with Human Resource Allocation -- On the Use of Run Time Distributions to Evaluate and Compare Stochastic Local Search Algorithms -- Estimating Bounds on Expected Plateau Size in MAXSAT Problems -- A Theoretical Analysis of the k-Satisfiability Search Space -- Loopy Substructural Local Search for the Bayesian Optimization Algorithm -- Running Time Analysis of ACO Systems for Shortest Path Problems -- Techniques and Tools for Local Search Landscape Visualization and Analysis -- Short Papers -- High-Performance Local Search for Solving Real-Life Inventory Routing Problems -- A Detailed Analysis of Two Metaheuristics for the Team Orienteering Problem -- On the Explorative Behavior of MAX–MIN Ant System -- A Study on Dominance-Based Local Search Approaches for Multiobjective Combinatorial Optimization -- A Memetic Algorithm for the Multidimensional Assignment Problem -- Autonomous Control Approach for Local Search -- EasyGenetic: A Template Metaprogramming Framework for Genetic Master-Slave Algorithms -- Adaptive Operator Selection for Iterated Local Search -- Improved Robustness through Population Variance in Ant Colony Optimization -- Mixed-Effects Modeling of Optimisation Algorithm Performance.
520 ## - SUMMARY, ETC.
Summary, etc Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer programming.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data structures (Computer science).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information theory.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information retrieval.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer architecture.
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 Computer science.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Programming Techniques.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Structures and Information Theory.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Storage Representation.
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 Computer Science Logic and Foundations of Programming.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Stützle, Thomas.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Birattari, Mauro.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hoos, Holger H.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642037504
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642037528
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Theoretical Computer Science and General Issues,
-- 2512-2029 ;
Volume number/sequential designation 5752
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-642-03751-1">https://doi.org/10.1007/978-3-642-03751-1</a>
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Koha item type eBooks-CSE-Springer

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