UT Arlington Faculty: Victoria Chen, Bill Corley
Collaborators: Bruce Beck, Feng Jiang
Ph.D. Students: Julia Tsai (Georgia Tech 2002), Prashant Tarun (2008)
Funding: U.S. EPA 2000-05
Topics: Evaluation of wastewater treatment technologies, multiple objectives, multiple-stage decision-making
Description: The goal of a city’s wastewater infrastructure is to control the disposal of urban effluents, traditionally so as to achieve clean water, although increasingly to achieve the recovery and recycling of resources. We have developed a multiple stage, multiple objective decision-making framework based on stochastic dynamic programming for evaluating current and emerging wastewater treatment technologies in the presence of uncertainty. The continuous state variables consist of several attributes in the liquid and solid material undergoing treatment, and categorical state variables are created to model dependencies between the levels (stages) of treatment. The liquid treatment process allows up to 11 levels, and the solid treatment process allow up to 6 levels. The objectives consider economic cost, nutrient recovery, robustness, size, odor emissions, and global desirability.
- Tarun, P. K., V. C. P. Chen, and H. W. Corley (2014). “Divergence Behaviour of the Successive Geometric Mean Method of Pairwise Comparison Matrix Generation for a Multiple Stage, Multiple Objective Optimization Problem.” Journal of Multi-Criteria Decision Analysis, 21, pp. 197–208. COSMOS Technical Report 12-07.
- Tarun, P. K., V. C. P. Chen, H. W. Corley, and F. Jiang (2011). “Optimizing Selection of Technologies in a Multiple Stage, Multiple Objective Wastewater Treatment System.” Journal of Multi-Criteria Decision Analysis, 18, pp. 115–142. COSMOS Technical Report 09-03.
- Tarun, P. K., V. C. P. Chen, H. W. Corley, and F. Jiang (2008). “Incorporating Decision Makers’ Inputs in a Dynamic Multiple Stage, Multiple Objective Model.” In Proceedings of the 2008 IE Research Conference, Vancouver, BC, Canada, May.
- Tsai, J. C. C. and V. C. P. Chen (2005). “Flexible and Robust Implementations of Multivariate Adaptive Regression Splines within a Wastewater Treatment Stochastic Dynamic Program.” Quality and Reliability Engineering International, 21, pp. 689–699.
- Tsai, J. C. C., V. C. P. Chen, J. Chen, and M. B. Beck (2004). “Stochastic Dynamic Programming Formulation for a Wastewater Treatment Decision-Making Framework.” Annals of Operations Research, Special Issue on Applied Optimization under Uncertainty, 132, pp. 207–221.