Review of Latest Advances in Nature-Inspired Algorithms for Optimization of Activated Sludge Processes

The activated sludge process (ASP) is the most widely used biological wastewater treatment system. Advances in research have led to adoption of Artificial Intelligence (AI), particular, Nature-Inspired Algorithm (NIA) techniques such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) optimize systems. This has aided reducing complexity computational time ASP modelling. paper covers latest NIAs discusses advantages limitations each algorithm compared more traditional algorithms that been utilized over last few decades. were assessed based on whether they looked at real/ideal plant (WWTP) data (and efficiency) outperformed optimizing ASP. While conventional (GAs), (PSO), Ant Colony (ACO) found be successfully employed optimization techniques, newer Whale (WOA), Bat (BA), Intensive Weed (IWO) achieved similar results ASP, while also having certain unique advantages.