Handbook of Approximation Algorithms and Metaheuristics
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...
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CRC Press
2009
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| Truy cập trực tuyến: | http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1540 |
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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. |
| format |
Book |
| author |
Gonzalez, Teofilo |
| spellingShingle |
Gonzalez, Teofilo Handbook of Approximation Algorithms and Metaheuristics |
| author_facet |
Gonzalez, Teofilo |
| author_sort |
Gonzalez, Teofilo |
| title |
Handbook of Approximation Algorithms and Metaheuristics |
| title_short |
Handbook of Approximation Algorithms and Metaheuristics |
| title_full |
Handbook of Approximation Algorithms and Metaheuristics |
| title_fullStr |
Handbook of Approximation Algorithms and Metaheuristics |
| title_full_unstemmed |
Handbook of Approximation Algorithms and Metaheuristics |
| title_sort |
handbook of approximation algorithms and metaheuristics |
| publisher |
CRC Press |
| publishDate |
2009 |
| url |
http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1540 |
| _version_ |
1757670442926080000 |
| spelling |
oai:scholar.dlu.edu.vn:DLU123456789-15402009-12-04T01:38:19Z Handbook of Approximation Algorithms and Metaheuristics Gonzalez, Teofilo 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. 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 2009-12-04T01:38:19Z 2009-12-04T01:38:19Z 2007 Book http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1540 en application/rar CRC Press |