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 ishybridized with two of the most reliable heuristic search methods, namely geneticalgorithm (ga) and ant colony optimization algorithm (acoa), for the simultaneousoptimal design of layout and size of pumped and/or gravity sewer networks. ghcamodel has recently been proposed by the authors for the optimal size determination ofthe sewer network with xed layout. the model has been shown to be able to optimallydesign pumped and/or gravity sewer networks, if required. in proposed hybrid models, theheuristic search algorithms are used to create trial layout for the network while ghca isused to design the network by determining the pipe diameters, pipe slopes, drop height, andpump height, if required. an ad-hoc engineering based method is used to determine feasiblelayouts by ga, while a tree growing algorithm (tga) is used to construct feasible layoutusing acoa. the proposed hybrid models are tested against two benchmark sewer networksand the comparison of results to those of some existing methods indicates that proposedmodels, and in particular the acoa-ghca method, are more ecient and eective thansome alternative methods for the optimal design of layout and size of sewer networks.