Cities: , Stop after stable iterations.
Population: , Mutation %: , % to Mate: , Eligible Pop %:
Population: , Mutation %: , % to Mate: , Eligible Pop %:
Ready.
Genetic algorithms simulate genetics and evolution. A solution to a problem is viewed as a "life form", or a "Chromosome". Then many solutions are created. The better solutions live to "mate" with other "better solutions". Therefore, the whole population gradually evolves to an ideal solution.
The "Traveling Salesman Problem" (TSP) is a common problem applied to artificial intelligence. The TSP presents the computer with a number of cities, and the computer must compute the optimal path between the cities. This applet uses a genetic algorithm to produce a solution to the "Traveling Salesman Problem".