TY - GEN
T1 - Optimal operation of soil aquifer treatment systems under uncertainty using genetic algorithms
AU - Tang, Aihua
AU - Mays, Larry
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 1999
Y1 - 1999
N2 - 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.
AB - 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.
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U2 - 10.1061/40430(1999)176
DO - 10.1061/40430(1999)176
M3 - Conference contribution
AN - SCOPUS:84904661208
SN - 0784404305
SN - 9780784404300
T3 - WRPMD 1999: Preparing for the 21st Century
BT - WRPMD 1999
PB - American Society of Civil Engineers (ASCE)
T2 - 29th Annual Water Resources Planning and Management Conference, WRPMD 1999
Y2 - 6 June 1999 through 9 June 1999
ER -