Efficient resizing and topological optimization of real-worldwater distribution networks in a multi-criteriadecision-making framework

“This study addresses complex multi-objective optimization challenges in large-scale, real-world water distribution networks (WDNs). The primary objectivesare to improve a water quality index (water age) and network resilience byoptimizing pipe diameters and network topology as decision variables. Theproposed approaches leverage the non-dominated sorting genetic algorithmII (NSGA-II) producing Pareto optimal alternatives for water utility decision-makers. To enhance computational convergence runtime and solution quality ofoptimization, novel techniques are employed. These include advanced NSGA-IIconstraint handling, search space reduction, graph theory-based formulation ofdecision variables, constraints, and objective functions, as well as multi-stage andhydraulic-free optimization strategies. Furthermore, soft constraints are relaxedand integrated into Pareto decision-making spaces to provide a comprehen-sive, multi-criteria decision-making framework. The approaches are applied to areal case study, and the results demonstrate optimization performance improve-ments, with efficiency increasing by approximately 20% (in terms of convergencespeed). Additionally, water age is reduced by 52% while achieving favorableresults in the hydraulic and topological criteria. These findings highlight theeffectiveness of the proposed methodologies in addressing WDN optimizationchallenges.”

(Citation: Minaei, A., Zecchin, A.C., Hajibabaei, M., et.al. – Efficient resizing and topological optimization of real-worldwater distribution networks in a multi-criteriadecision-making framework – Computer-Aided Civil and Infrastructure EngineeringEarly View (2025) – https://doi.org/10.1111/mice.70036 – (Open Access))