Water is becoming an essential commodity for human life and is one of the most important natural resources. Public water utilities provide more than 90 percent of the world's water supply today, so a safe water distribution system is critical for any city. The importance, huge capital cost of the system, and growing city size lead to water distribution network optimization. In this work, we propose and compare two algorithms to optimize the water network design of a new neighborhood of our city, where a public cooperative is in charge of this utility. Consequently, two metaheuristic algorithms based on Tabu Search and Simulated Annealing (SOTS and HSA, respectively) arise to minimize the investment cost of a water distribution network. The experimentation suggests that both algorithms optimize the investment cost, with results that are comparable.