A novel optimization framework for efficiently identifying high-quality Pareto-optimal solutions: maximizing resilience of water distribution systems under cost constraints

• A new framework is proposed to efficiently identify high-quality Pareto solutions . • A tailored objective function maximizes network resilience under cost constraints. • A new selection strategy handles two types of constraints without penalty functions. • Explorative search behavior limits MOEAs in finding low-cost optimal solutions. • Increasing main pipes while reducing branch pipes enhances network resilience. The design of water distribution systems (WDS) presents a classic multi-objective engineering optimization problem, involving maximizing network resilience within cost constraints. While multi-objective evolutionary algorithms (MOEAs) perform well in small WDS optimizations, they often yield…

• NN
  National Natural Science Foundation of China

  Award: 52260011
• AB
  Applied Basic Research Key Project of Yunnan