Optimal groundwater remediation design by chance-constrained programming

Yu Feng Lin, Charles S. Sawyer

Research output: Contribution to conferencePaperpeer-review

Abstract

Groundwater remediation optimization models for pump-and-treat technology were developed using a statistical methodology, Chance-Constrained Programming (CCP). The method accounted for uncertainty in the coefficients of the models. Several models were formulated that depended on which set of coefficients were considered uncertain. The CCP method transformed the probabilistic constraints to their deterministic equivalents which used less computer memory and storage locations. The resulting models were mixed-integer programming models. Results are presented that demonstrated the application of the models. The results showed that incorporating uncertainty into the groundwater optimization model using CCP could be a practical method for making decisions on well locations, pumping rates, and number of wells in groundwater remediation.

Original languageEnglish (US)
Pages174-179
Number of pages6
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 27th Congress of the International Association of Hydraulic Research, IAHR. Part C - San Francisco, CA, USA
Duration: Aug 10 1997Aug 15 1997

Other

OtherProceedings of the 1997 27th Congress of the International Association of Hydraulic Research, IAHR. Part C
CitySan Francisco, CA, USA
Period8/10/978/15/97

ASJC Scopus subject areas

  • General Engineering

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