Handbook of Approximation Algorithms and Metaheuristics (Chapman & Hall CRC Computer & Information Science Series)

✍ Scribed by Teofilo F. Gonzalez

• Publisher: Chapman and Hall/CRC
• Year: 2007
• Tongue: English
• Leaves: 1351
• Edition: 1
• Category: Library

✦ Synopsis

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical applications. It is the first book to comprehensively study both approximation algorithms and metaheuristics. Starting with basic approaches, the handbook presents the methodologies to design and analyze efficient approximation algorithms for a large class of problems, and to establish inapproximability results for another class of problems. It also discusses local search, neural networks, and metaheuristics, as well as multiobjective problems, sensitivity analysis, and stability. After laying this foundation, the book applies the methodologies to classical problems in combinatorial optimization, computational geometry, and graph problems. In addition, it explores large-scale and emerging applications in networks, bioinformatics, VLSI, game theory, and data analysis.Undoubtedly sparking further developments in the field, this handbook provides the essential techniques to apply approximation algorithms and metaheuristics to a wide range of problems in computer science, operations research, computer engineering, and economics. Armed with this information, researchers can design and analyze efficient algorithms to generate near-optimal solutions for a wide range of computational intractable problems.

✦ Table of Contents

86.2 Color Spaces for Quantization......Page 3
85.4 Design Requirements for a Reputation System......Page 5
86.4 Image-Dependent, Context-Free Quantization......Page 6
85.5.4 Motivation Is Not a Problem: Dissenting Views......Page 8
85.5.5 Other Design Issues......Page 9
85.6.1 Complaints-Based Trust......Page 10
85.7 Conclusions and Future Work......Page 14
References......Page 19
86.1 Introduction......Page 1
85.2 Applications of Reputation Management......Page 2
85.6.2 EigenTrust......Page 11
86.5.2 Feedback-Based Quantization......Page 12
85.6.4 ROCQ......Page 13
References......Page 16
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References......Page 15
References......Page 17
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85.5.2 Second-Order Reputation......Page 7
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86.3 Image-Independent Quantization......Page 4
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51.7.4 Finding Low-Cost kappa-VCSS and kappa-ECSS in Planar Graphs......Page 20
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75.3.2.2 A (1 + epsilon) Polynomial-Approximation Scheme......Page 21
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