Intelligent Optimized Decision-Support System for Sewer Network Assets Improvement

Sewer assets are subject to deterioration due to environmental and physical factors. Existing industry practices show that there is a lack of proper scheduling of rehabilitation projects based on optimized solutions that would improve infrastructure performance while minimizing the total life cycle costing (TLCC). Improper asset management may lead to catastrophic failures that result in sewage spills. This paper aims at enhancing the methodologies adopted in capital improvement plans (CIPs) to identify certain intervention actions that will maintain existing infrastructure and restore the overall performance. The methodology utilized the particle swarm optimization (PSO) method to maximize the overall network performance (ONP) and minimize the TLCC, given a number of constraints. A nonlinear deterioration was also considered during the study period through the application of the Weibull distribution analysis. The framework was deployed on a number of pipelines and manholes in the Royal Gardens neighborhood in Edmonton, Alberta. The near-optimum budget required to restore the sewer network to an ONP of 2.11 was $1.126 million. This optimization tool will aid decision makers in planning for future interventions to limit sudden collapses and future spills.