Optimal operation of soil aquifer treatment systems under uncertainty using genetic algorithms

Aihua Tang, Larry Mays

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A stochastic optimization model with chance-constraints has been developed to account for parameter uncertainty and an enhanced genetic algorithm is applied to solve the optimal operation problem of the SAT systems. The model identifies the optimal operation schedules, i.e., the water application time and drying time for the infiltration basins to obtain a maximum hydraulic loading rate. Hydraulic criteria are satisfied using bound constraints on the water content. There are incorporated chance constraints to account for the uncertainty due to physical variability and parameter measurement.

Original languageEnglish (US)
Title of host publicationWRPMD 1999
Subtitle of host publicationPreparing for the 21st Century
PublisherAmerican Society of Civil Engineers (ASCE)
ISBN (Print)0784404305, 9780784404300
DOIs
StatePublished - Jan 1 1999
Event29th Annual Water Resources Planning and Management Conference, WRPMD 1999 - Tempe, AZ, United States
Duration: Jun 6 1999Jun 9 1999

Publication series

NameWRPMD 1999: Preparing for the 21st Century

Other

Other29th Annual Water Resources Planning and Management Conference, WRPMD 1999
CountryUnited States
CityTempe, AZ
Period6/6/996/9/99

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Tang, A., & Mays, L. (1999). Optimal operation of soil aquifer treatment systems under uncertainty using genetic algorithms. In WRPMD 1999: Preparing for the 21st Century (WRPMD 1999: Preparing for the 21st Century). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/40430(1999)176