Dimensionamento econômico de redes de distribuição de água considerando os custos de manutenção e de implantação

Abstract

We present an approach for project optimization problem of networks water supply (RDA), considering the deployment cost (CI) and the cost of maintenance (MC) simultaneously applying a multi-population and multiobjective algorithm. An RDA can be seen as a graph whose edges are the conduits and the vertices are the nodes. Choose the diameters that make the most economical network given the restrictions techniques is a combinatorial problem for which direct methods may become unworkable when considering increasing numbers snippets. The optimization problem is tackled to minimize both CI and CM of an RDA, considering it to the cost of conduits according to their diameters and lengths. To carry out optimization was developed the evolutionary algorithm (EA) Hybrid Multi-Island-niched Pareto Genetic Algorithm (MINPGA), merge output adapted from a multi-population algorithm, MIIGA, another multi-objective algorithm based on Niche Pareto, the NPGA. How hydraulic simulator was used Environment Protection Agency Network Engine Tool (EPANET). The optimization scheme of Network By Evolutionary Algorithm (ONEBEAR) has been developed and applied to three different network sizes and layouts, one of with 666 snippets. A computer program was written to implement the ONEBEAR, connecting the EPANET to MINPGA, allowing desired optimization. It has been shown, and the importance of considering the cost of maintenance over the life of a RDA address the feasibility of multi-objective optimization problem using an AE multi-population. The scheme shown robustness and flexibility, solving the problem of optimization for both branched networks and for looped networks and a network with 666 excerpts. The Pareto front generated for each problem showed the dominant solutions considered viable. The viability of the networks was checked for compliance with technical requisite minimum pressure per node, calculated by EPANET. The smaller networks and CI