Riassunto:
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.
Contenuti:
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
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