Genetic Algorithms and TSP Thomas Jefferson Computer Research Project by Karl Leswing

Genetic Algorithms Effective in Optimization Problems Classified as a global search heuristic Inspired by Evolutionary Biology Inheritance Mutation Selection Crossover

Traveling Salesman Given a number of cities and the costs of traveling from any city to any other city, what is the cheapest round-trip rout that visits each city exactly once and then returns to the starting city.

Traveling Salesman Continued Dynamic Programming down to O((n^2)*2^n)‏ Find Near Optimal Solutions

Current Work

Current Work Continued Double Point Crossover Roulette Selection Unique Fitness Algorithm Single Point Mutation Mutation Rate Variable Effectiveness Solve 50 City TSP in less than one minute

Ant Colony Optimization Pheromone Trail Evaporation Rate Effective for dynamically changing graphs Useful for network routing and urban transportation systems

3 Dimensions Attempted Open GL with Pipe Attempted Jogl Given Up Java Bindings for OpenGl Given Up Work on Comparison of global search hueristics

Extensions Finish my ant colony optimization (ACO)‏ Brute Force Automated Test Particle Swarm Optimization (PSO)‏ Neural Networking