Handbook of Approximation Algorithms and Metaheuristics: Methologies and Traditional Applications, Volume 1, 2nd Edition (Hardback) book cover

Handbook of Approximation Algorithms and Metaheuristics

Methologies and Traditional Applications, Volume 1, 2nd Edition

Edited by Teofilo F. Gonzalez

Chapman and Hall/CRC

798 pages | 150 B/W Illus.

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Hardback: 9781498770118
pub: 2018-05-23
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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.

Table of Contents

Part 1: Basic Methodologies

1. Introduction, Overview and Definitions

Teofilo F. Gonzalez

2. Basic Methodologies and Applications

Teofilo F. Gonzalez

3. Restriction Methods

Teofilo F. Gonzalez

4. Greedy Methods

Samir Khuller, Balaji Raghavachari, and Neal E. Young

5. Recursive Greedy Methods

Guy Even

6. Local Ratio

Dror Rawitz

7. LP Rounding and Extensions

Daya Ram Gaur and Ramesh Krishnamurti

8. Polynomial Time Approximation Schemes

Hadas Shachnai and Tami Tamir

9. Rounding, Interval Partitioning and Separation

Sartaj Sahni

10. Asymptotic Polynomial Time Approximation Schemes

Rajeev Motwani, Liadan O’Callaghan, and An Zhu

11. Randomized Approximation Techniques

Sotiris Nikoletseas and Paul Spirakis

12. Distributed Approximation Algorithms via LP-duality and Randomization

Devdatt Dubhashi, Fabrizio Grandoni, and Alessandro Panconesi

13. Empirical Analysis of Randomised Algorithms

Holger H. Hoos and Thomas St¨utzle

14. Reductions that Preserve Approximability

Giorgio Ausiello and Vangelis Th. Paschos

15. Differential Ratio Approximation

Giorgio Ausiello and Vangelis Th. Paschos

Part 2: Local Search, Neural Networks, and Meta-heuristics

16. Local Search

Roberto Solis-Oba and Nasim Samei

17. Stochastic Local Search

Holger H. Hoos and Thomas St¨utzle

18. Very Large Neighborhood Search

Ravindra K. Ahuja, ¨Olem Ergun, James B Orlin, and Abraham P Punnen

19. Reactive Search: Machine Learning for Memory-Based Heuristics

Roberto Battiti and Mauro Brunato

20. Neural Networks

Bhaskar DasGupta, Derong Liu, and Hava T. Siegelmann

21. Principles and Strategies of Tabu Search

Fred Glover, Manuel Laguna, and Rafael Mart´ı

22. Evolutionary Computation

Guillermo Leguizam´on, Christian Blum, and Enrique Alba

23. An Introduction to Ant Colony Optimization

Marco Dorigo and Krzysztof Socha

Part 3: Multiobjective Optimization, Sensitivity Analysis and Stability

24. Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization: A Review

Lu´ıs Paquete and Thomas St¨utzle

25. Reoptimization of Hard Optimization Problems

Hans-Joachim B¨ockenhauer, Juraj Hromkovic, and Dennis Komm

26. Sensitivity Analysis in Combinatorial Optimization

David Fern´andez-Baca and Balaji Venkatachalam

27. Stability of Approximation

Hans-Joachim B¨ockenhauer, Juraj Hromkovic, and Sebastian Seibert

Part 4: Traditional Applications

28. Performance Guarantees for One Dimensional Bin Packing

J´anos Csirik and Gy¨orgy D´osa

29. Variants of Classical One Dimensional Bin Packing

J´anos Csirik and Csan´ad Imreh

30. Variable Sized Bin Packing and Bin Covering

J´anos Csirik

31. Multidimensional Packing Problems

Leah Epstein and Rob van Stee

32. Practical Algorithms for Two-dimensional Packing of Rectangles

Shinji Imahori, Mutsunori Yagiura, and Hiroshi Nagamochi

33. Practical Algorithms for Two-dimensional Packing of General Shapes

Yannan Hu, Hideki Hashimoto, Shinji Imahori, and Mutsunori Yagiura

34. Prize Collecting Traveling Salesman and Related Problems

Giorgio Ausiello, Vincenzo Bonifaci, Stefano Leonardi, and Alberto Marchetti-Spaccamela

35. A Development and Deployment Framework for Distributed Branch and Bound

Peter Cappello and Chris Coakley

36. Approximations for Steiner Minimum Trees

Ding-Zhu Du andWeili Wu

37. Practical Approximations of Steiner Trees in Uniform Orientation Metrics

Andrew B. Kahng, Ion Mandoiu, and Alexander Zelikovsky

38. Algorithms for Chromatic Sums, Multicoloring, and Scheduling Dependent

Jobs Magn´us M. Halld´orsson and Guy Kortsarz

39. Approximation Algorithms and Heuristics for Classical Planning

Jeremy Frank, Minh Do, and J. Benton

40. Generalized Assignment Problem

WeiWu, Mutsunori Yagiura, and Toshihide Ibaraki

41. Probabilistic Greedy Heuristics for Satisfiability Problems

Rajeev Kohli and Ramesh Krishnamurti

42. Linear Ordering Problem

Celso S. Sakuraba and Mutsunori Yagiura

43. Submodular FunctionsMaximization Problems

Niv Buchbinder andMoran Feldman

About the Editor

Teofilo Gonzalez is a professor of computer science at the University of California, Santa Barbara.

About the Series

Chapman & Hall/CRC Computer and Information Science Series

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Computer Engineering
MATHEMATICS / Arithmetic