In this paper, a hybrid model, GA–GHCA, composed of the genetic algorithm (GA) and the general hybrid cellular automata (GHCA) is proposed for the efficient and effective optimal design of pumped sewer networks with fixed layout. The GHCA model was recently introduced by the authors with considerable success for the optimal design of sewer networks. Two alternative versions of the GA–GHCA model are proposed. In the first approach, the pump locations and the corresponding pumping heads are decided by the GA model, while the diameter and nodal cover depths of the network pipes are optimally determined by the GHCA model considering the predefined pump locations and their pumping heights defined by the GA. In the second model, however, only the pump locations are decided by the GA model and for each GA individual, the network characteristics including the pipe diameters, pipe nodal cover depths, and the pumping heights at the predefined locations are determined by the GHCA model. The proposed GA–GHCA model is tested against a benchmark example of pumped sewer network and the results are presented and compared to those of the existing methods. The results indicate that the proposed method is more efficient and effective than alternative methods for the optimal design of pumped sewer networks.
Impact of Self-Cleansing Criteria Choice on the Optimal Design of Sewer Networks in South America
