Optimum design of booster chlorination systems in water distribution networks by using the shuffled antlion optimization approach

Chlorine is one of the most used disinfectants in urban water distribution networks, both globally and in Türkiye. Its widespread use as a disinfectant is primarily attributed to its low cost, ease of application, and effectiveness in inactivating a significant proportion of pathogenic microorganisms. Chlorination is typically performed through centralized injections, usually at the outlet of the treatment plant or the inlet of the main reservoir. However, in such single-point chlorination applications, chlorine concentrations tend to be high near the injection point, while a significant decrease is observed toward the distal ends of the network. To address this imbalance, the establishment of additional booster chlorination stations has become necessary. These stations play a critical role in ensuring a homogeneous distribution of chlorine throughout the network and in maintaining chlorine concentrations within predefined upper and lower limits. Furthermore, to minimize the overall system cost, it is essential to determine the optimal number, locations, and injection dosages of these additional booster chlorination stations. Within the scope of this thesis, a simulation–optimization approach has been developed to ensure the sustainable maintenance of water quality standards in water distribution networks by determining the number, spatial locations, and chlorine injection dosages of additional booster chlorination stations. In the simulation phase of the proposed approach, the EPANET model, which is developed by the United States Environmental Protection Agency (US-EPA), has been employed to simulate the hydrodynamic flow and chlorine transport processes within the pipelines. For the optimization phase, the SHuffled Ant Lion Optimization (SHALO) approach which is an enhanced variant of the Ant Lion Optimization (ALO) approach inspired by the hunting behavior of antlions in nature, has been utilized. The applicability of the proposed simulation–optimization approach has been evaluated using a benchmark water distribution network that is widely used in the literature. As part of the evaluation, the proposed approach was solved under identical conditions and compared statistically with both previous studies and the classical ALO approach. The results indicated that the SHALO approach demonstrated superior performance in terms of both solution quality and computational efficiency.