Different hydraulic analysis conditions for sewer network design optimisation problem using three different evolutionary algorithms

In this paper, the efficiency of considering the constant and varying Manning coefficient for a hydraulic analysis model on the optimal solution of sewer network design optimisation problem is studied. To solve sewer network design optimisation problem, here, different formulations are proposed using genetic algorithm, discreet and continues ant colony optimisation algorithms. In all proposed formulations, the nodal cover depths of the sewer network are taken as decision variables of the problem. Furthermore, for both ant-based algorithms two different formulations are proposed using unconstrained and constrained versions of these algorithms. The constrained versions of these algorithms are proposed here for the explicit satisfaction of the minimum pipe slope constraint leading to smaller search space. Two benchmark test examples are solved here using proposed formulations and the results are presented and compared with other available results. Comparison of the results shows the superiority of considering varying Manning coefficient condition for hydraulic analysis model. Furthermore, the results show the superiority of continues ant colony optimisation algorithm and especially the constrained version of it to optimally solve the sewer network design optimisation problem.