Parallel Evolutionary Algorithm for Designing Water Distribution Networks to Minimize Background Leakage

Abstract

Leaks in water distribution systems waste energy and water resources, increase damage to infrastructure, and may allow contamination of potable water. This research develops an evolutionary algorithm-based approach to minimize the cost of water loss, new infrastructure, and operations that reduce background leakage. A new design approach is introduced that minimizes capital and operational costs, including energy and water loss costs. Design decisions identify a combination of infrastructure improvements, including pipe replacement and valve installment, and operation rules for tanks and pumps. Solution approaches are developed to solve both a single-objective and multiobjective problem formulation. A genetic algorithm and a nondominated sorting genetic algorithm are implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure-reducing valves, and pipe diameters for replacing pipes. The evolutionary algorithm approaches identify solutions that minimize water loss due to leakage, operational costs, and capital costs, while maintaining pressure at nodes and operational feasibility for tanks and pumps. Solutions are compared to identify a recommended design. The framework is demonstrated to redesign a water distribution system for an illustrative case study, C-Town.