Comparison of a genetic algorithm and mathematical programming to the design of groundwater cleanup systems | Zendy

Aly Alaa H. | Zendy; Peralta Richard C. | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

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.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research