Circulatory system-based optimization algorithm with dynamic penalty function for optimum design of large-scale water distribution networks

Water distribution networks (WDNs) are a crucial component of urban infrastructure, and their optimization plays a vital role in minimizing construction costs. However, existing heuristic algorithms for WDN optimization often rely on specific parameters, limiting their performance and hindering their applicability to diverse network configurations, particularly in large-scale systems. To address this challenge, a novel method called circulatory system-based optimization (CSBO) is proposed, which minimizes the need for algorithm-specific parameters and achieves optimal designs across WDNs of various scale. The impact of a dynamic penalty function tailored to pressure constraints on the optimal design is also investigated. This study encompasses the optimization of the Goyang and combined gravity networks and the large-scale Balerma irrigation and Kang and Lansey networks under identical conditions. The results of the standard and dynamic CSBO approaches prove that the proposed algorithms have a superior performance, particularly in convergence rate and stability, compared to previous methods.