Multi-objective Programming for Water Pollution Control in a Tidal River Based on GA

This paper deals with a case study about catchment of the Shenzhen River,a tidal river,within which there are five wastewater treatment plants(WWTPs).With the objectives to curtail the total operation cost of the wastewater treatment and optimize the pollutants removal rates of the plants,a multi-objective optimization approach,integrated with cost function of WWTPs,a dynamic water quality model and Non-dominated Sorting Genetic Algorithm II(NSGA-II),was developed.Results suggested various schemes for achieving minimum operation cost of the WWTPs with different non-compliance rates of the water quality in different control river's sections in the upper,middle and downstream reaches respectively.Thus,the study offers a variety of scenarios for the pollution control of the river catchment according to the existing economic and technical circumstances as well as the space and temporal distributions of the river's water quality.