A GA-HP Model for the Optimal Design of Sewer Networks

Abstract

This paper illustrates the application of a new model combined Genetic Algorithm with Heuristic Programming (GA-HP) technique in order to establish the optimal design for sewer networks. The objective is to minimise the construction cost function, which is represented by the depth of excavation and pipe diameter. The proposed GA-HP model has achieved the optimum design task in two stages. Firstly, the Genetic Algorithm (GA) was applied to obtain the diameters of the pipes needed for the preliminary design of the network. Secondly, Heuristic Programming (HP) preliminary designs were used to obtain the optimal slope for those pipes and to determine other characteristics such as the velocity, relative depth of water, excavation depths and total cost of the network. A MATLAB code was used to perform the GA-HP optimisation modelling. The performance of three different selection methods, four different crossover methods and different population sizes is examined with the proposed model, to determine their impact on convergence behaviour. The proposed GA-HP model is tested using some benchmark examples of sewer networks from the literature. The results show that the GA-HP model is superior to all previous methods and may be more efficient in the design of large networks.