1. Evolutionary Computing and the Traveling Salesman
By Sam Mulder

2. Overview Local optimization for the TSP
Evolutionary Computing for the TSP
Combining local search with EAs
Proposed algorithm
Neural algorithm for comparison
Results
Conclusions

3. Local Optimization for the TSP
Lin-Kernighan Algorithm
Double bridges
Chained Lin-Kernighan Algorithm

4. Double Bridge

5. Evolutionary Computing for the TSP
Non-Lamarkian EAs
Mutation and Crossover
Very small problem sizes
Low quality results

6. Combining Local Search with EAs
Chained Lin-Kernighan revisited
Visualization of search space
Adding Lamarkian learning
Scatter Search

7. Proposed Algorithm
Population
Crossover
Mutation
Learning
Competition

8. Neural Algorithm for Comparison
Divide and Conquer using ART
Self-Organizing Maps on sub-problems
Lin-Kernighan optimization
Merging tours

9. Results Speed vs Quality 100 city problem 1000 city problem

10. Conclusions EA = parallel Chained Lin-Kernighan
Parallel implementation may allow scaling
Local Search + EA = unsolved problem
Need to try divide and conquer + EA

11. Results cont. Chained Lin-Kernighan Proposed Algorithm
Neural Clustering