Development of a cost function for residential subdivisions through genetic algorithms

The study of urbanization, and the water distribution networks that supply water to urban areas, has led to new approaches for evaluating the distribution systems that serve residential subdivisions. The present study aims to expand the evaluation method commonly applied by using genetic algorithms to add the actual hydraulic constraints required by Tucson Water in Arizona to an optimization model. Furthermore, an alternative calculation method utilizing a heuristic preoptimization tool coupled with a greedy algorithm is compared with the genetic algorithm results. The improved model is capable of achieving a near optimal solution, one that is comparable to the genetic algorithm results and should minimize the cost of constructing and operating a water distribution network. Preliminary results show that population density has little effect on the total cost and that area is the driving factor in cost. In addition, the slope increases the rate at which these two parameters increase the cost, making high-density areas much more cost effective with respect to the operation of water distribution systems. Finally, the main assumption, which considers residential subdivisions as rectangular networks, is explored by comparing the generated networks against their realistic counterparts. Results showed that the realistic networks cost more than the generated networks.