چكيده لاتين :
In this paper, an extension of classical waste-load allocation models for river water quality
management is presented to determine the monthly treatment or removal fraction of wastewater
to evaporation ponds. The dimensionality of the problem, which is due to a large number
of decision variables, is tackled by developing a new GA based optimization model, which is
called a Sequential Dynamic Genetic Algorithm (SDGA). This is a deterministic multi-objective
optimization model, which is linked to an unsteady water quality simulation model. The model
minimizes the total losses incurred during the optimization time horizon, including the treatment
or removal fraction costs and the costs associated with the deviation from water quality standards.
The proposed model has been used for the water quality management and salinity reduction of
the Karoon River in Iran. The results show the proposed model can effectively reduce the
computational burden of the seasonal waste-load allocation problem. It is also shown that the
seasonal waste-load allocation can significantly reduce the number and duration of standards
violations.
