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Comparison of a genetic algorithm and mathematical programming to the design of groundwater cleanup systems
Author(s) -
Aly Alaa H.,
Peralta Richard C.
Publication year - 1999
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/1998wr900128
Subject(s) - groundwater , nonlinear programming , mathematical optimization , aquifer , integer programming , computer science , genetic algorithm , norm (philosophy) , nonlinear system , environmental science , algorithm , mathematics , engineering , geotechnical engineering , physics , quantum mechanics , political science , law
We present and apply a new simulation/optimization approach for single‐ and multiple‐planning period problems in groundwater remediation. Instead of the traditional control locations for contaminant concentrations, we use an L ∞ norm as a global measure of aquifer contamination (CMAX). We use response‐surface constraints to represent CMAX within the optimization model. We compare the performance of formal mixed integer nonlinear programming and a genetic algorithm for several optimization scenarios.