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Chance-constrained fuzzy optimization model for enhancing facultative ponds: A case study at Bantul wastewater treatment plant
Summary
Researchers proposed a chance-constrained fuzzy optimization model for wastewater treatment in facultative ponds, applying it to the Bantul domestic wastewater treatment plant in Indonesia to maximize treatment volume under uncertain biological oxygen demand conditions.
In this study, a new optimization model is proposed in the form of chance-constrained fuzzy uncertain programming, which is used to optimize facultative ponds' performance in wastewater treatment. The observed wastewater parameter was the Biological Oxygen Demand (BOD). The developed model was based on the situation faced by the decision-maker in which some parameters, such as the BOD degradation rate and the wastewater load were fuzzy with some membership functions. Under this uncertainty, the decision-maker desired to maximize the wastewater treatment volume with the appropriate safety margin for the objective and constraint functions by utilizing chance-based policies. This study was conducted at Bantul domestic wastewater treatment plant located in Yogyakarta, Indonesia. The optimal decisions for the debit of the wastewater and the processing time were achieved. It is concluded that the proposed model successfully solved the given problem, hence it is utilizable by the decision-maker.
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