A Multi-Objective Optimization Decision Support Model for Renewal Planning of Sewer Networks

Municipalities are facing unprecedented challenges due to ageing of the sewer networks, increasing demand levels, climbing renewal deficit, and inadequate renewal budgets. Sustainable management of sewer networks requires the adoption of proactive renewal strategies that can maximize the return on investment by optimizing budget allocation, maximizing asset performance, minimizing risk of failure, and minimizing life-cycle costs. Clearly, a multi-objective approach is needed in order to find the best trade-off between these conflicting criteria.

This paper will discuss the development of a novel multi-objective optimization approach and a decision support system for optimal renewal planning of sewer networks. A genetic algorithm (GA)-based multi-objective optimization approach is used to find a Pareto front and identify a set of feasible solutions, where each solution recommends a set of sewers for the renewal each year, along with the associated costs. The preference of one solution over the others depends on the budget available and the corresponding gain in the overall network condition and risk levels. The paper will also present the application of the proposed approach and software on the sewer network in Regina, SK.