Planning Rehabilitation Strategy of Sewer Asset Using Fast Messy Genetic Algorithm

Abstract

The present study suggests a model for planning sewer asset rehabilitation strategy, developed with an optimization algorithm. The fast messy genetic algorithm was used to suggest an optimized rehabilitation strategy with an objective function to minimize total costs of sewer rehabilitation and I/I treatment. The developed model was tested in a selected case study network of Banpo in Seoul, South Korea. Within a reasonable and finite number of searching, it was successful to obtain optimum rehabilitation schedules and costs for both cases of optimization problems that were for individual sewer lines and for group of sewer lines. It is expected that this model can contribute as a decision making tool in prioritising of sewer rehabilitation projects and estimating the optimal budget for officials of municipalities or local government. Also, this model can act as a supplemental tool in conducting the cost-effective analysis for sewer rehabilitation projects for engineering consultants.