Abstarct: Water distribution networks are important urban installations which designing and programming need large investments. So that optimization is used as a tool for minimizing the cost correlated with water distribution systems. In the last few decades many researchers have been attracted by evolutionary methods for optimization; so that in water distribution networks Genetic and Ant colony algorithms have been substituted for the techniques baxsed on linear and nonlinear programming. In this project genetic and ant colony algorithms are used in order to optimize water distribution networks. In the use of GA for optimization at first, search space would be reduced by means of water velocity parameter and path concept in pipes. Optimum design solution using GA is governed by several factors such as population size, fitness functions, penalty functions, GA operators, number of generations and the most more important the size of the search space. Reducing search space obtains an optimization solution in less time and increase probability of gaining global optimum. In GA, Binary and Gray coding with roulette wheel and tournament selection operators, and one point, two point and uniform crossover operators, has been used for comprising. In parallel with GA optimization baxsed on search space reduction, ant colony algorithm has been used for optimization of water distribution networks. ACOA has been inspired by the behavior of ants for finding food sources. In this algorithm elitist ant system has been used each iteration, and three point crossover and mutation operators have been utilized.