Pseudo-genetic Model Optimization for Rehabilitation of Urban Storm-water Drainage Networks

Abstract One of the main concerns in many cities is the need to rehabilitate or expand their drainage systems. Increasing rainfall intensities related with climate change, uncontrolled growth and excessive waterproofing of cities causes that original drainage networks design have became insufficient. Inadequate drainage networks make necessary to develop rehabilitation models of existing networks. This models should be compatible with them. This paper presents an optimization methodology to generate different solutions for the existing network improvement. This methodology uses as starting point a model of the actual storm water network. In this paper the SWMM model is used to perform the hydraulic analysis of the network. Also a Pseudo-Genetic Algorithm (PGA) is used as optimization engine. This PGA model has been previously developed for other hydraulic optimization problems. The developed optimization model includes as decision variables: the rehabilitation or replacement of existing pipes, the potential location of stormwater retention tanks at certain points and their size, the initial state of the existing pumping units, and the start and stop levels of each pump. To evaluate each solution during the optimization process it has been necessary to develop a series of costs functions: a) a cost function or damage function relating the flood level and associated damage costs; b) a cost function of stormwater retention tanks which relates the investment cost in the construction of the tank with its volume; c) a pipeline rehabilitation cost function that relates the cost of rehabilitation or replacement of a pipe with its nominal diameter; d) a cost function for each pump unit giving the cost of the electrical energy consumed during the operation. Finally, the methodology developed has been applied to solve the flooding problems of a small section of the drainage network of the city of Bogota (Colombia).