A step forward in the management of multiple wastewater streams by using an ant colony optimization-based method with bounded pheromone

• ACO algorithms showed efficient management of dynamic inputs in wastewater systems.
• A procedure for maximizing industrial discharges in treatment systems.
• Use of bounded pheromone trials to improve search optimization.

Wastewater treatment systems (WTSs) have as an objective to efficiently treat the wastewater flows that they receive. Wastewater treatment plants (WWTP) process optimization is generally based on biological process optimization, which is usually related to the quantity and quality of the WWTP inflows. The inflow contributions sometimes destabilize the biological system due to flow and nutrient load limitations, with a higher impact in small and decentralized systems. Their management is a complex task due to the multiple constituents and different flows, but it should be the first step for a general, optimal and comprehensive optimization.Ant colony optimization (ACO) has demonstrated the ability to solve these complex problems, as metaheuristic methodologies, using an iterative and probabilistic procedure. This work proposes to solve the treatment influent composition by using two ACO algorithms. Both algorithms apply bounded pheromone trails to resolve the failures in the search for an optimal solution limited by inflow constraints. The results present high efficacy in maximizing the total wastewater inflow that fulfils all the constraints and improving the WWTP management with different inflows and constraints.

In wastewater treatment systems, the management of multiple streams (with multiple contaminants) is an essential factor to ensure the optimum efficiency. To minimize the high complexity of this task, two ant colony optimization algorithms with bounded pheromone trails have been successfully evaluated.Figure optionsDownload high-quality image (205 K)Download as PowerPoint slide