Wastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied to a Sequencing Batch Reactor (SBR) in a biological Wastewater Treatment Plant (WWTP). Based on real data records, the ASM2d model of biological processes and the aeration system model are applied. The two-layer hierarchical control structure described in previous works has been extended by an additional optimization layer, used to determine the optimal operating parameters of the SBR reactor (sequence and durations of individual phases), the optimal desired trajectory of dissolved oxygen, and the optimal parameters of the adaptive controller operating in the upper control layer. A large number of different deterministic and non-deterministic optimization algorithms were tested. Finally, the Artificial Bee Colony (ABC) algorithm and the Direct Search Algorithm (DSA) were applied. In the proposed control structure, the lower control layer is the Internal Model Control (IMC) based airflow controller. Results of simulation tests for the wastewater treatment plant case study are presented. As an optimization result, the process operations have become more efficient and the electrical energy consumption has been reduced. (C) 2019 Elsevier Ltd. All rights reserved.