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Handbook of Approximation Algorithms and Metaheuristics: Methologies and Traditional Applications, Volume 1 2nd edition [Kõva köide]

Edited by (University of California, Santa Barbara, USA)
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Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.

Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems.

Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more.

About the Editor

Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Preface xi
Contributors xiii
1 Introduction, Overview, and Notation
1(26)
Teofilo F. Gonzalez
SECTION I Basic Methodologies
2 Basic Methodologies and Applications
27(16)
Teofilo F. Gonzalez
3 Restriction Methods
43(12)
Teofilo F. Gonzalez
4 Greedy Methods
55(16)
Samir Khuller
Balaji Raghavachari
Neal E. Young
5 Recursive Greedy Methods
71(16)
Guy Even
6 Local Ratio
87(26)
Dror Rawitz
7 LP Rounding and Extensions
113(12)
Daya Ram Gaur
Ramesh Krishnamurti
8 Polynomial Time Approximation Schemes
125(32)
Hadas Shachnai
Tami Tamir
9 Rounding, Interval Partitioning and Separation
157(16)
Sartaj Sahni
10 Asymptotic Polynomial Time Approximation Schemes
173(16)
Rajeev Motwani
Liadan O'Callaghan
An Zhu
11 Randomized Approximation Techniques
189(14)
Sotiris Nikoletseas
Paul Spirakis
12 Distributed Approximation Algorithms via LP-Duality and Randomization
203(22)
Devdatt Dubhashi
Fabrizio Grandoni
Alessandro Panconesi
13 Empirical Analysis of Randomised Algorithms
225(18)
Holger H. Hoos
Thomas Stiitzle
14 Reductions That Preserve Approximability
243(16)
Giorgio Ausiello
Vangelis Th. Paschos
15 Differential Ratio Approximation
259(18)
Giorgio Ausiello
Vangelis Th. Paschos
SECTION II Local Search, Neural Networks, and Metaheuristics
16 Local Search
277(20)
Roberto Solis-Oba
Nasim Samei
17 Stochastic Local Search
297(14)
Holger H. Hoos
Thomas Stiitzle
18 Very Large-Scale Neighborhood Search: Theory, Algorithms, and Applications
311(16)
Ravindra K. Ahuja
Ozlem Ergun
James B. Orlin
Abraham P. Punnen
19 Reactive Search: Machine Learning for Memory-Based Heuristics
327(18)
Roberto Battiti
Mauro Brunato
20 Neural Networks
345(16)
Bhaskar DasGupta
Derong Liu
Hava T. Siegelmann
21 Principles and Strategies of Tabu Search
361(18)
Fred Glover
Manuel Laguna
Rafael Marti
22 Evolutionary Computation
379(16)
Guillermo Leguizamdn
Christian Blum
Enrique Alba
23 An Introduction to Ant Colony Optimization
395(16)
Marco Dorigo
Krzysztof Socha
SECTION III Multiobjective Optimization, Sensitivity Analysis, and Stability
24 Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization: A Review
411(16)
Luis Paquete
Thomas Stiitzle
25 Reoptimization of Hard Optimization Problems
427(28)
Hans-Joachim Bockenhauer
Juraj Hromkovif
Dennis Komm
26 Sensitivity Analysis in Combinatorial Optimization
455(18)
David Ferndndez-Baca
Balaji Venkatachalam
27 Stability of Approximation
473(18)
Hans-Joachim Bockenhauer
Juraj Hromkovic
Sebastian Seibert
SECTION IV Traditional Applications
28 Performance Guarantees for One Dimensional Bin Packing
491(28)
Janos Csirik
Gyorgy Dosa
29 Variants of Classical One Dimensional Bin Packing
519(20)
Janos Csirik
Csanad Imreh
30 Variable Sized Bin Packing and Bin Covering
539(14)
Janos Csirik
31 Multidimensional Packing Problems
553(18)
Leah Epstein
Rob van Stee
32 Practical Algorithms for Two-Dimensional Packing of Rectangles
571(14)
Shinji Imahori
Mutsunori Yagiura
Hiroshi Nagamochi
33 Practical Algorithms for Two-Dimensional Packing of General Shapes
585(26)
Yannan Hu
Hideki Hashimoto
Shinji Imahori
Mutsunori Yagiura
34 Prize Collecting Traveling Salesman and Related Problems
611(18)
Giorgio Ausiello
Vtncenzo Bonifaci
Stefano Leonardi
Alberto Marchetti-Spaccamela
35 A Development and Deployment Framework for Distributed Branch-and-Bound
629(12)
Peter Cappello
Christopher James Coakley
36 Approximations for Steiner Minimum Trees
641(16)
Ding-Zhu Du
Weili Wu
37 Practical Approximations of Steiner Trees in Uniform Orientation Metrics
657(14)
Andrew B. Kahng
Ion Mdndoiu
Alexander Zelikovsky
38 Algorithms for Chromatic Sums, Multicoloring, and Scheduling Dependent Jobs
671(14)
Magnus M. Hallddrsson
Guy Kortsarz
39 Approximation Algorithms and Heuristics for Classical Planning
685(28)
Jeremy Frank
Minh Do
J. Benton
40 Generalized Assignment Problem
713(24)
Wei Wu
Mutsunori Yagiura
Toshihide Ibaraki
41 Linear Ordering Problem
737(16)
Celso S. Sakuraba
Mutsunori Yagiura
42 Submodular Functions Maximization Problems
753(36)
Niv Buchbinder
Moran Feldman
Index 789
Teofilo Gonzalez is a professor of computer science at the University of California, Santa Barbara.