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We develop multiobjective optimization models to
simultaneously minimize biosolids odors as well as
wastewater treatment process and biosolids
distribution costs. A weighting method and constraint
method were employed to find tradeoff, so called
Pareto optimal, points between costs and odors. Schur s decomposition and special order set type two
variables were used to approximate the product of two
decision variables. A Dantzig-Wolfe decomposition
technique was successfully applied to break apart and
solve a large optimization model encountered in this
dissertation.Using the Blue Plains advanced
wastewater treatment plant located in Washington, DC
as a case study, we find several Pareto optimal
points between costs and odors where different
treatments (e.g., lime addition) and biosolids
distribution (e.g., to what reuse fields biosolids
should be applied) strategies should be employed.
This model can be used proactively by any typical
advanced wastewater treatment plants to produce the
least malodorous biosolids at minimal costs.
simultaneously minimize biosolids odors as well as
wastewater treatment process and biosolids
distribution costs. A weighting method and constraint
method were employed to find tradeoff, so called
Pareto optimal, points between costs and odors. Schur s decomposition and special order set type two
variables were used to approximate the product of two
decision variables. A Dantzig-Wolfe decomposition
technique was successfully applied to break apart and
solve a large optimization model encountered in this
dissertation.Using the Blue Plains advanced
wastewater treatment plant located in Washington, DC
as a case study, we find several Pareto optimal
points between costs and odors where different
treatments (e.g., lime addition) and biosolids
distribution (e.g., to what reuse fields biosolids
should be applied) strategies should be employed.
This model can be used proactively by any typical
advanced wastewater treatment plants to produce the
least malodorous biosolids at minimal costs.