Abstract: Objective: The objective of the study was to present the enhancement model of the Simple Standard Genetic Algorithm (SGA). 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 it is called the Human Community Based Genetic Algorithm (HCBGA). Methodology: The Traveling Salesman Problem (TSP) was used as a test problem, which is a minimization problem. This test shows the differences of each model based on the human community based genetic algorithm’s best fit values and averages in different generations. Tests were conducted over three models, the simple standard genetic algorithm, the Island Genetic Algorithm (IGA) 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 in relation to slowing the convergence of solutions are significantly better in the enhanced human community based genetic algorithm than the other two, the simple standard genetic algorithm and the island genetic algorithm. Conclusion: The enhanced human community based genetic algorithm indicates 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.