Part1: 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
Part2: 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
Part3: 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
Part4: 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