Stochastic Dynamic Programming Formulation for a Wastewater Treatment Decision-Making Framework

Julia Tsai (), Victoria Chen (), M. Beck and Jining Chen

Annals of Operations Research, 2004, vol. 132, issue 1, 207-221

Abstract: In this paper, a decision-making framework (DMF) based on stochastic dynamic programming (SDP) is presented for a wastewater treatment system, consisting of a liquid treatment line with eleven levels and a solid treatment line with six levels (Chen and Beck, 1997). A continuous-state SDP solution approach based on the OA/MARS method (Chen, Ruppert, and Shoemaker, 1999) is employed, which provides an efficient method for representing a wide range of possible influent conditions. The DMF is used to evaluate current and emerging technologies for the multi-level liquid and solid lines of the wastewater treatment system. At each level, one technology unit is selected out of a set of options which includes the empty unit. The DMF provides a comparison on possible technologies for screening which types of technologies may best be further developed in order for an urban wastewater infrastructure to be judged progressively more sustainable. The results indicate that one or a pair of technologies are dominant in each level. The cheap, lower-technology unit processes receive a mixed review. Some of them are selected as the most promising technology units while the others are not considered as good candidates. Copyright Kluwer Academic Publishers 2004

Keywords: dynamic programming; orthogonal arrays; Latin hypercubes; regression splines; wastewater treatment (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1023/B:ANOR.0000045283.86576.62

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