Over the past few decades, various evolutionary algorithms (EAs) have been applied to the optimization design of water distribution systems (WDSs). An important research area is to compare the performance of these EAs, thereby offering guidance for the selection of the appropriate EAs for practical implementations. Such comparisons are mainly based on the final solution statistics and, hence, are unable to provide knowledge on how different EAs reach the final optimal solutions and why different EAs performed differently in identifying optimal solutions. To this end, this paper aims to compare the real-time searching behaviour of three widely used EAs, which are genetic algorithms (GAs), the differential evolution (DE) algorithm and the ant colony optimization (ACO). These three EAs are applied to five WDS benchmarking case studies with different scales and complexities, and a set of five metrics are used to measure their run-time searching quality and convergence properties. Results show that the run-time metrics can effectively reveal the underlying searching mechanisms associated with each EA, which significantly goes beyond the knowledge from the traditional end-of-run solution statistics. It is observed that the DE is able to identify better solutions if moderate and large computational budgets are allowed due to its great ability in maintaining the balance between the exploration and exploitation. However, if the computational resources are rather limited or the decision has to be made in a very short time (e.g., real-time WDS operation), the GA can be a good choice as it can always identify better solutions than the DE and ACO at the early searching stages. Based on the results, the ACO performs the worst for the five case study considered. The outcome of this study is the offer of guidance for the algorithm selection based on the available computation resources, as well as knowledge into the EA’s underlying searching behaviours.

This paper presents a many-objective analysis framework to handle large real-world water distribution system design problems (WDSDP), which is a typically difficult infrastructure engineering optimization problem type. Six objectives are formulated, focusing on economic, structural and functional aspects in the operation and management of the water distribution system (WDS), and solved by Borg, which is one state-of-the-art multi-objective evolutionary algorithm (MOEA) in water resources. The framework comprehensively analyzes and reveals the underlying trade-offs among many objectives, thereby facilitating the selection of the most appropriate design solutions for real-world WDSs. A real-world WDSDP with 1278 decision variables is used to demonstrate the effectiveness of the proposed framework, and results show that it can clearly reveal the complex trade-offs among these six different objectives, and it greatly enhances the understanding of the underlying characteristics of Pareto-front solutions. The insights have great practical implications for optimally designing large real-world WDS problems.

This study investigated the degradation kinetics and product generation of ofloxacin (OFL) in the pipe network under different pipe materials, flow rate, pH, free chlorine concentration and temperature. The experiments done in the beaker and pipe network were compared. The results showed that the reaction rate of OFL chlorination with free chlorine increased with the increase of the free chlorine concentration in the pipe network and deionized water, and the degradation efficiency of OFL in the pipe network was higher than that in the deionized water, satisfying the second-order dynamics model. The degradation rate under different pHs was: neutral > acidic > alkaline. The influence of the flow rate is not significant while the influence of the pipe materials and temperature is obvious. The degradation rate of OFL increased with the increase of the temperature, indicating that the OFL degradation was an endothermic process. A liquid chromatograph-mass spectrometer (LC-MS) was used to detect the chlorination intermediates, and the results showed that the piperazine ring was the main group involved in the chlorination reaction, and the main point involved in the chlorination reaction was the N4 atom on the piperazine ring. We also found that, as the reaction time increases, the concentrations of trihalomethanes (THMs) and haloacetic acids (HAAs) increase and THMs mainly exist in the form of trichloromethane (TCM) while HAAs mainly exist in the form of monochloroacetic acid (MCAA).