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Multiple‐objective optimization of drinking water production strategies using a genetic algorithm
Author(s) -
Vink Kees,
Schot Paul
Publication year - 2002
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 - 10.1029/2000wr000034
Subject(s) - drawdown (hydrology) , mathematical optimization , production (economics) , genetic algorithm , multi objective optimization , linkage (software) , pareto principle , computer science , mathematics , engineering , economics , biochemistry , chemistry , geotechnical engineering , gene , aquifer , groundwater , macroeconomics
Finding a strategy that allows economically efficient drinking water production at minimal environmental cost is often a complex task. A systematic trade‐off among the costs and benefits of possible strategies is required for determining the optimal production configuration. Such a trade‐off involves the handling of interdependent and nonlinear relations for drawdown‐related objective categories like damage to wetland vegetation, agricultural yield depression, reduction of river base flow rates, and soil subsidence. We developed a method for multiple‐objective optimization of drinking water production by combining Busacker and Gowen 's [1961] “minimum cost flow” procedure for optimal use of the transport network with a genetic algorithm (GA) for optimization of other impacts. The performance of the GA was compared with analytically determined solutions of a series of hypothetical case studies. Pareto‐optimality and uniqueness of solutions proved to be effective fitness criteria for identifying trade‐off curves with the GA.