Development of a Stochastic Programming Model for Design and Optimization of Activated-Sludge Wastewater-Treatment System Considering Efforts of Uncertain Factors

In this study, an improved interval two-stage programming (ITSP) model is applied for design and optimization of an activated-sludge process (ASP) wastewater-treatment system under uncertainty. Improved ITSP integrates full-infinite programming and two-stage programming into an interval linear programming framework. Improved ITSP is capable of addressing multiple uncertainties that exist in related costs, impact factors, and system objectives, which can be expressed as determinates and crisp interval values. The modeling approach allows uncertainties and decision makers' aspirations to be directly communicated into the optimization process and resultant solutions. This is the first attempt to apply ITSP to an ASP wastewater-treatment system, in which pollutant discharge can be controlled in whole aspects. Results indicate that reasonable solutions would be generated. This model is applicable for a conventional ASP wastewater-treatment system without any nitrification because of the oxygen demand for ammonia oxidation. It can help decision makers to identify desired policies under various economic and system constraints by generating decision alternatives, which can also coordinate the conflicting interactions among economic cost, system efficiency, and pollutant mitigation. (C) 2017 American Society of Civil Engineers.