Background and Objective: An enhancement model of the Simple Standard Genetic Algorithm is being presented. This model is based on custom, behavior, age, gender and pattern of human community. It is an enhanced structured population approach for genetic algorithm so called the Human Community Based Genetic Algorithm. The Traveling Salesman Problem is used as a test problem, which is a minimization problem. Methodology: This test show differences of each model based on the Human Community Based Genetic Algorithm’s best fit values and averages in different generations. Tests are conducted over three models, the Simple Standard Genetic Algorithm, the Island Genetic Algorithm and the enhanced Human Community Based Genetic Algorithm. Results: Best fit solutions in different populations of different generations show better performance of the enhanced Human Community Based Genetic Algorithm over the other two models the Simple Standard Genetic Algorithm and the Island Genetic Algorithm. In addition, Results towards slowing the convergence of solutions are significantly better in the enhanced Human Community Based Genetic Algorithm than both the Simple Standard Genetic Algorithm and the Island Genetic Algorithm. Conclusion: The enhanced Human Community Based Genetic Algorithm indicate that a population structure model based on the rules of marriage concepts can clearly improve the performance of the Simple Standard Genetic Algorithm and the Island Genetic Algorithm.