The problem of optimal layout is one of the most difficult problems. This is due to the large size of the search space, which expands rapidly as the size of the network increases. This paper introduces an adaptive procedure to improve the efficiency of genetic algorithm (GA) formulation in GA-TGA optimization model of the optimum layout design of sewer networks. Adaptive strategy helps the designer develop adaptive genetic algorithms in which method operators are systematically adapted to the constraints of the layout problem. The adaptive selection operator keeps the genetic algorithm in feasible region of the search space and consequently improve the performance of optimization in terms of speed. The formulation of selection and crossover lead to not need to discard or repair unfeasible solutions or apply penalty factors to the cost function as commonly used in the principles of genetic algorithms. Four different selection methods will be used with the GA. In MATLAB code, the optimization model implemented. Benchmark example and case study of sewer networks are used to test the present method. This method has proven to be effective in terms of solution optimality and the resulting convergence characteristics. Additionally, the method proves itself capable of finding an optimal, or near optimal solution.