The effectiveness of wastewater systems with high-industrial effluent input requires avoiding temporary overloads due to influent volumes and/or pollutant loads that exceed the system's treatment capacity. The multiagent paradigm is shown to be a suitable methodology for managing all information related to the state of the entire system to apply optimal influent assignment criteria. However, to be efficient, this methodology requires a prioritization process to assign priorities to different influent classes. A novel approach is proposed for solving this complex issue using a combinatorial optimization procedure with multiple constraints that is implemented when the treatment system lacks the capacity to accept all of its influent. The metaheuristic method applied is an ant colony optimization-based method, and the solution is achieved using two distinct algorithms with different processes for updating the pheromone trail. The results illustrate their usefulness, even when industrial effluents exhibit large fluctuations in their pollutant concentrations. © 2011 American Institute of Chemical Engineers AIChE J, 58: 3070–3079, 2012
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