An optimization model of sewage rehabilitation

Abstract

Due to low visibility, sewer systems are difficult to monitor, maintain and rehabilitate. To prevent failures, environmental pollution, and wastewater treatment overflow, regular rehabilitation of sewage is necessary. However, sewage rehabilitation usually costs an immense amount of money and is hampered by a limited budget. Thus, efficient planning of maintenance and rehabilitation for sewage upkeep is demanded. In this paper, an optimization model has been built to find an appropriate rehabilitation strategy consisting of a rehabilitation method and a substitute material for each pipe failure under a limited budget. The optimization model was designed to search for a Pareto curve (or trade‐off front) consisting of a set of optimal solutions with desirable rehabilitation effectiveness at the least cost. This paper employs genetic algorithms (GA) to obtain a Pareto curve at a low computation cost for large and complex sewer systems. This optimization model was applied to a sewer system in the 15^th district of Kaohsiung City, Taiwan. Compared with the experts’ manual estimation, the optimization model saved about 20% of the rehabilitation cost for Kaohsiung City.