Route Optimization Through Evolutionary Programming

Simulating the logic of natural evolution has been proposed as a method for generating artificial intelligence through the automation of inductive inference. Here, Evolutionary Programming is used for route optimization using a traveling salesman problem. This approach is compared to using the greedy algorithm on a fifty city problem. The percentage of tours that are superior to the evolved solution is estimated.