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Handbook of Approximation Algorithms and Metaheuristics

Contemporary and Emerging Applications

Edited by: Teofilo F. Gonzalez

Print publication date:  May  2018
Online publication date:  May  2018

Print ISBN: 9781498769990
eBook ISBN: 9781351235426
Adobe ISBN:

10.1201/9781351235426
 Cite  Marc Record

Book description

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

Prelims Download PDF
Chapter  1:  Introduction, Overview, and Notation Download PDF
Chapter  2:  Approximation Schemes for Minimum-Cost k-Connectivity Problems in Geometric Graphs  Download PDF
Chapter  3:  Dilation and Detours in Geometric Networks Download PDF
Chapter  4:  The Well-Separated Pair Decomposition and Its Applications Download PDF
Chapter  5:  Covering with Unit Balls Download PDF
Chapter  6:  Minimum Edge-Length Rectangular Partitions Download PDF
Chapter  7:  Automatic Placement of Labels in Maps and Drawings Download PDF
Chapter  8:  Complexity, Approximation Algorithms, and Heuristics for the Corridor Problems Download PDF
Chapter  9:  Approximate Clustering Download PDF
Chapter  10:  Maximum Planar Subgraph Download PDF
Chapter  11:  Disjoint Paths and Unsplittable Flow Download PDF
Chapter  12:  The k-Connected Subgraph Problem Download PDF
Chapter  13:  Node-Connectivity Survivable Network Problems Download PDF
Chapter  14:  Optimum Communication Spanning Trees Download PDF
Chapter  15:  Activation Network Design Problems Download PDF
Chapter  16:  Stochastic Local Search Algorithms for the Graph Coloring Problem Download PDF
Chapter  17:  On Solving the Maximum Disjoint Paths Problem with Ant Colony Optimization Download PDF
Chapter  18:  Efficient Approximation Algorithms in Random Intersection Graphs Download PDF
Chapter  19:  Approximation Algorithms for Facility Dispersion Download PDF
Chapter  20:  Cost-Efficient Multicast Routing in Ad Hoc and Sensor Networks Download PDF
Chapter  21:  Approximation Algorithm for Clustering in Mobile Ad-Hoc Networks Download PDF
Chapter  22:  Topology Control Problems for Wireless Ad Hoc Networks Download PDF
Chapter  23:  QoS Multimedia Multicast Routing Download PDF
Chapter  24:  Overlay Networks for Peer-to-Peer Networks Download PDF
Chapter  25:  Data Broadcasts on Multiple Wireless Channels: Exact and Time-Optimal Solutions for Uniform Data and Heuristics for Nonuniform Data  Download PDF
Chapter  26:  Strategies for Aggregating Time-Discounted Information in Sensor Networks Download PDF
Chapter  27:  Approximation and Exact Algorithms for Optimally Placing a Limited Number of Storage Nodes in a Wireless Sensor Network Download PDF
Chapter  28:  Approximation Algorithms for the Primer Selection, Planted Motif Search, and Related Problems  Download PDF
Chapter  29:  Dynamic and Fractional Programming-Based Approximation Algorithms for Sequence Alignment with Constraints Download PDF
Chapter  30:  Approximation Algorithms for the Selection of Robust Tag SNPs Download PDF
Chapter  31:  Large-Scale Global Placement  Download PDF
Chapter  32:  Histograms, Wavelets, Streams, and Approximation Download PDF
Chapter  33:  Color Quantization Download PDF
Chapter  34:  A GSO-Based Swarm Algorithm for Odor Source Localization in Turbulent Environments Download PDF
Chapter  35:  Digital Reputation for Virtual Communities Download PDF
Chapter  36:  Approximation for Influence Maximization Download PDF
Chapter  37:  Approximation and Heuristics for Community Detection Download PDF
Index Download PDF
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