Multi‐Objective Optimization Design of Irrigation Pipe Networks Based on a Hybrid Harmony Search Algorithm

ABSTRACT This study presents a multi‐objective optimization method for the design of irrigation pipe networks based on a hybrid harmony search algorithm (HEV‐HS). The primary motivations for this study are the challenges of uneven flow, water pressure distribution and frequent pipe failures commonly encountered in large‐scale irrigation pipe network systems. The proposed method minimizes the investment cost of the pipe network and the variance of the surplus head at nodes. A generalized multi‐objective optimization model was formulated to enhance the economic efficiency and operational reliability of irrigation networks. The proposed HEV‐HS algorithm combines harmony search with energy valley optimization and incorporates dynamic adaptive step‐size adjustment alongside an iterative control factor mechanism to increase the ability of the algorithm to escape local optima and improve the quality of the solution set. Simulation tests demonstrated the effectiveness of the proposed method in solving high‐dimensional, complex optimization problems, achieving superior convergence speed and solution quality. An application involving a drip irrigation project in Xinjiang, China shows that the optimized scheme reduces investment costs by 5.1% and decreases the variance of the node surplus hydraulic head by 7.5%. These results confirm the validity and practicality of the method and its potential to improve pressure uniformity and cost efficiency in irrigation pipe network design.