Stochastic Optimization/Simulation of Centralized Liquid Industrial Waste Treatment

Abstract

A stochastic optimization‐simulation method is presented for delineating least‐cost treatment sequences for a centralized liquid industrial waste treatment facility. A dynamic programming model performs the optimization. The function of the model is to delineate least‐cost treatment sequences that will produce an acceptable effluent stream qualify given a probabilistically‐generated influent waste regime. The model is structured to permit the following user‐determined options: waste types and respective volumes in the waste inventory; specific contaminants within each waste type; contaminant‐specific probability density functions for waste strength; unit treatment processes including performance efficiencies and related costs; and individual contaminant effluent standards. The stochastic dynamic programming model served as a screening device, identifying unit treatment processes and sequences of processes with favorable cost‐effectiveness attributes. The treatment paths thus identified were further analyzed and refined using stochastic simulation techniques.