In this exercise, we attempt to utilize genetic algorithms to find an optimal, but not perfect, solution to the traveling salesman problem. A genetic algorithm emulates nature in its optimization process. Nature uses several mechanisms which have led to the emergence of new species and still better adapted to their environments. The laws which react to species evolution have been known by the research of Charles Darwin in the last century: Genetic algorithms are powerful methods of optimization that utilize these rules defined by evolution in their process to find a pseudo-optimal answer. These algorithms were modeled on the evolution of species. The genetic algorithm utilizes the properties of genetics such as selection, crossover, mutation.