Layout and size optimization of sewer networks by hybridizing the GHCA model with heuristic algorithms

In this paper, a General Hybrid Cellular Automata (GHCA) model is hybridized with two of the most reliable heuristic search methods, namely Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACOA), for the simultaneous optimal design of layout and size of pumped and/or gravity sewer networks. GHCA model has recently been proposed by the authors for the optimal size determination of the sewer network with xed layout. The model has been shown to be able to optimally design pumped and/or gravity sewer networks, if required. In proposed hybrid models, the heuristic search algorithms are used to create trial layout for the network while GHCA is used to design the network by determining the pipe diameters, pipe slopes, drop height, and pump height, if required. An ad-hoc engineering based method is used to determine feasible layouts by GA, while a Tree Growing Algorithm (TGA) is used to construct feasible layout using ACOA. The proposed hybrid models are tested against two benchmark sewer networks and the comparison of results to those of some existing methods indicates that proposed models, and in particular the ACOA-GHCA method, are more ecient and eective than some alternative methods for the optimal design of layout and size of sewer networks.