Evolutionary Computation-Based Decision-Making Framework for Designing Water Networks to Minimize Background Leakage

摘要

This research minimizes the impact of leaks on the operation of the system to reduce lost water while meeting typical management goals. A genetic algorithm approach is implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure control valves, and pipe diameters for replacing pipes. It identifies solutions that minimize water loss, operational costs, and capital costs, while maintaining pressure at nodes and operational feasibility for tanks. Multiple problem formulations are solved that use alternative objective functions and allow varying degrees of freedom in the decision space. The methodology is demonstrated to identify a water distribution system re-design for the C-Town case study.