Handbook of Approximation Algorithms and Metaheuristics, Second Edition: Methodologies and Traditional Applications

ISBN-13: 9780367571580 / Angielski / Miękka / 2020 / 798 str.

Teofilo F. Gonzalez

Opis

Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, and other metaheuristics.

Spis treści

Part 1: Basic Methodologies  1. Introduction, Overview and Definitions  2. Basic Methodologies and Applications  3. Restriction Methods  4. Greedy Methods  5. Recursive Greedy Methods  6. Local Ratio  7. LP Rounding and Extensions  8. Polynomial Time Approximation Schemes  9. Rounding, Interval Partitioning and Separation  10. Asymptotic Polynomial Time Approximation Schemes  11. Randomized Approximation Techniques  12. Distributed Approximation Algorithms via LP-duality and Randomization  13. Empirical Analysis of Randomised Algorithms  14. Reductions that Preserve Approximability  15. Differential Ratio Approximation  Part 2: Local Search, Neural Networks, and Meta-heuristics  16. Local Search  17. Stochastic Local Search  18. Very Large Neighborhood Search  19. Reactive Search: Machine Learning for Memory-Based Heuristics  20. Neural Networks  21. Principles and Strategies of Tabu Search  22. Evolutionary Computation  23. An Introduction to Ant Colony Optimization  Part 3: Multiobjective Optimization, Sensitivity Analysis and Stability  24. Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization: A Review  25. Reoptimization of Hard Optimization Problems  26. Sensitivity Analysis in Combinatorial Optimization  27. Stability of Approximation  Part 4: Traditional Applications  28. Performance Guarantees for One Dimensional Bin Packing  29. Variants of Classical One Dimensional Bin Packing  30. Variable Sized Bin Packing and Bin Covering  31. Multidimensional Packing Problems  32. Practical Algorithms for Two-dimensional Packing of Rectangles  33. Practical Algorithms for Two-dimensional Packing of General Shapes  34. Prize Collecting Traveling Salesman and Related Problems  35. A Development and Deployment Framework for Distributed Branch and Bound  36. Approximations for Steiner Minimum Trees  37. Practical Approximations of Steiner Trees in Uniform Orientation Metrics  38. Algorithms for Chromatic Sums, Multicoloring, and Scheduling Dependent  39. Approximation Algorithms and Heuristics for Classical Planning  40. Generalized Assignment Problem  41. Probabilistic Greedy Heuristics for Satisfiability Problems  42. Linear Ordering Problem  43. Submodular FunctionsMaximization Problems

O autorze

Teofilo Gonzalez is a professor of computer science at the University of California, Santa Barbara.