Covariance Matrix Adaptation for Multi-objective Optimization
Evolutionary Computation
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This paper describes the use of a multi-objective evolution strategy in tuning a fuzzy controller which is used in sewage treatment plants. The controller adjusts the oxygenation in the aeration tank to support biological processes, which reduce nutrients. Globally optimal settings are unknown and up to now the settings are made by a specialist equipped with a large amount of background knowledge. We successfully approximated the pareto-optimal set of solutions considering given constraints and three objectives using a wastewater simulation software. Evolution was able to find the settings proposed by a human expert as well as an interesting parameter niche, the so called simultaneous intermittent denitrification, which promises energy savings.