Handbook of Approximation Algorithms and Metaheuristics

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ISBN 9781584885504
Cat# C5505
 

Features

  • Describes basic methodologies that include restriction, greedy, relaxation, rounding, primal-dual, local search, transformation, and metaheuristics
  • Explains polynomial time and fully polynomial time approximation schemes, including standard, asymptotic, and randomized
  • Reviews approximation algorithms for bin packing, the traveling sales person problem, and Steiner trees
  • Discusses computational geometry and graph applications, such as triangulations, pair decompositions, partitioning, maximum planar subgraphs, edge disjoint paths and unsplittable flow, and communication spanning trees
  • Presents the latest algorithmic applications, including wireless ad hoc networks, microarray analysis, and global routing
  • Summary

    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

    PREFACE

    BASIC METHODOLOGIES
    Introduction, Overview, and Notation
    Basic Methodologies and Applications
    Restriction Methods
    Greedy Methods
    Recursive Greedy Methods
    Linear Programming
    LP Rounding and Extensions
    On Analyzing Semidefinite Programming Relaxations of Complex
    Quadratic Optimization Problems
    Polynomial-Time Approximation Schemes
    Rounding, Interval Partitioning, and Separation
    Asymptotic Polynomial-Time Approximation Schemes
    Randomized Approximation Techniques
    Distributed Approximation Algorithms via LP-Duality and Randomization
    Empirical Analysis of Randomized Algorithms
    Reductions that Preserve Approximability
    Differential Ratio Approximation
    Hardness of Approximation

    LOCAL SEARCH, NEURAL NETWORKS, AND METAHEURISTICS
    Local Search
    Stochastic Local Search
    Very Large-Scale Neighborhood Search: Theory, Algorithms, and Applications
    Reactive Search: Machine Learning for Memory-Based Heuristics
    Neural Networks
    Principles of Tabu Search
    Evolutionary Computation
    Simulated Annealing
    Ant Colony Optimization
    Memetic Algorithms

    MULTIOBJECTIVE OPTIMIZATION, SENSITIVITY ANALYSIS, AND STABILITY
    Approximation in Multiobjective Problems
    Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization: A Review
    Sensitivity Analysis in Combinatorial Optimization
    Stability of Approximation

    TRADITIONAL APPLICATIONS
    Performance Guarantees for One-Dimensional Bin Packing
    Variants of Classical One-Dimensional Bin Packing
    Variable, Sized Bin Packing and Bin Covering
    Multidimensional Packing Problems
    Practical Algorithms for Two-Dimensional Packing
    A Generic Primal-Dual Approximation Algorithm for an Interval Packing and Stabbing Problem
    Approximation Algorithms for Facility Dispersion
    Greedy Algorithms for Metric Facility Location Problems
    Prize-Collecting Traveling Salesman and Related Problems
    A Development and Deployment Framework for Distributed Branch and Bound
    Approximations for Steiner Minimum Trees
    Practical Approximations of Steiner Trees in Uniform Orientation Metrics
    Approximation Algorithms for Imprecise Computation Tasks with 0/1 Constraint
    Scheduling Malleable Tasks
    Vehicle Scheduling Problems in Graphs
    Approximation Algorithms and Heuristics for Classical Planning
    Generalized Assignment Problem
    Probabilistic Greedy Heuristics for Satisfiability Problems

    COMPUTATIONAL GEOMETRY AND GRAPH APPLICATIONS
    Approximation Algorithms for Some Optimal 2D and 3D Triangulations
    Approximation Schemes for Minimum-Cost k-Connectivity Problems in Geometric Graphs
    Dilation and Detours in Geometric Networks
    The Well-Separated Pair Decomposition and its Applications
    Minimum-Edge Length Rectangular Partitions
    Partitioning Finite d-Dimensional Integer Grids with Applications
    Maximum Planar Subgraph
    Edge-Disjoint Paths and Unsplittable Flow
    Approximating Minimum-Cost Connectivity Problems
    Optimum Communication Spanning Trees
    Approximation Algorithms for Multilevel Graph Partitioning
    Hypergraph Partitioning and Clustering
    Finding Most Vital Edges in a Graph
    Stochastic Local Search Algorithms for the Graph Coloring Problem
    On Solving the Maximum Disjoint Paths Problem with Ant Colony Optimization

    LARGE-SCALE AND EMERGING APPLICATIONS
    Cost-Efficient Multicast Routing in Ad Hoc and Sensor Networks
    Approximation Algorithm for Clustering in Ad Hoc Networks
    Topology Control Problems for Wireless Ad Hoc Networks
    Geometrical Spanner for Wireless Ad Hoc Networks
    Multicast Topology Inference and its Applications
    Multicast Congestion in Ring Networks
    QoS Multimedia Multicast Routing
    Overlay Networks for Peer-to-Peer Networks
    Scheduling Data Broadcasts on Wireless Channels: Exact Solutions and Heuristics
    Combinatorial and Algorithmic Issues for Microarray Analysis
    Approximation Algorithms for the Primer Selection, Planted Motif Search, and Related Problems
    Dynamic and Fractional Programming-Based Approximation Algorithms for Sequence Alignment with Constraints
    Approximation Algorithms for the Selection of Robust Tag SNPs
    Sphere Packing and Medical Applications
    Large-Scale Global Placement
    Multicommodity Flow Algorithms for Buffered Global Routing
    Algorithmic Game Theory and Scheduling
    Approximate Economic Equilibrium Algorithms
    Approximation Algorithms and Algorithm Mechanism Design
    Histograms, Wavelets, Streams, and Approximation
    Digital Reputation for Virtual Communities
    Color Quantization

    INDEX

    Editorial Reviews

    "Therefore the existence of a reference such as this Handbook of Approximation Algorithms and Metaheuristics is very welcome and useful . . . Experts can find inspiration for further work, while those not familiar with this issue can, in a very elegant way, start to learn it."

    – Kristina Šoric, in Zentralblatt Math, 2008

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