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Various optimization approaches have been proposed in the past three decades to address the design cost optimization problem of water distribution systems. However, recently, evolutionary algorithms have been preferred due to their ability to solve complex, nonlinear, and discrete optimization problems such as water distribution system design. This study proposes a hybrid model, HHG that integrates Grey Wolf Optimizer and Harris Hawk, which is linked with an EPANET hydraulic simulator to optimize the design cost of a water distribution system network. The HHG model’s performance is shown through three typical water distribution systems, namely the Two-loop network, Hanoi network and New York network. The results show that the HHG is a potential approach for solving water distribution system design costs with higher reliability, lower cost, and faster processing time than other conventional approaches.

Application of artificial intelligence algorithm to optimize the design of water distribution system