An adaptive Differential Evolution algorithm for Sewer Networks Design

A newly introduced Self-adaptive Differential Evolution algorithm via Generalized Opposition-Based Learning (SDE-GOBL) is applied to optimal design of two sewer networks. Every chromosome consists of the information of network layout. Select a feasible design which satisfies the constraints of velocity, slope and proportional water depth to get optimal cost through the algorithm. Two sewer optimization problems in which the pipe diameters are considered as the decision variables are solved by the SDE-GOBL algorithm. Comparisons with the previous works are made and the results show that the proposed algorithm performs better in terms of solution quality and efficiency.