The application of particle swarm optimization in sewer budget allocation

Abstract

Sewer assets require regular inspection and maintenance plans to avoid any disruption due to structural and operational defects. Therefore, decision-makers are required to allocate budgets to enhance the performance of sewer manholes and pipelines. However, several municipalities confront major constraints when planning for rehabilitation due to restricted funds to repair all defected assets. Current practices focus on sewer pipelines disregarding the systematic improvement of sewer manholes. The objective of this research is to provide a framework to implement the Particle Swarm Optimization (PSO) method to reach a near optimum solution that maximizes the overall network performance (ONP), considering pipelines and manholes, and minimizes the total life cycle costing. The constrained problem can be solved by examining four different decision variables. The application of PSO in sewer infrastructure shall enhance current practices to systematically plan for renewals. As a result, defective assets are lessened, and the risk of sewage exfiltration is significantly reduced.