Striking a balance: Long-term groundwater monitoring design for conflicting objectives

Striking a balance: Long-term groundwater monitoring design for conflicting objectives

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Article ID: iaor2006535
Country: United States
Volume: 130
Issue: 2
Start Page Number: 140
End Page Number: 149
Publication Date: Mar 2004
Journal: Journal of Water Resources Planning and Management
Authors: ,
Keywords: pareto-optimality
Abstract:

This study demonstrates the use of high-order Pareto optimization (i.e., optimizing a system for more than two objectives) on a long-term monitoring (LTM) application. The LTM application combines' quantile kriging and the nondominated sorted genetic algorithm-II (NSGA-II) to successfully balance four objectives: (1) minimizing sampling costs, (2) maximizing the accuracy of interpolated plume maps, (3) maximizing the relative accuracy of contaminant mass estimates, and (4) minimizing estimation uncertainty. Optimizing the LTM application with respect to these objectives reduced the decision space of the problem from a total of 500 million designs to a set of 1,156 designs identified on the Pareto surface. Visualization of a total of eight designs aided in understanding and balancing the objectives of the application en route to a single compromise solution. This study shows that high-order Pareto optimization holds significant potential as a tool that can be used in the balanced design of water resources systems.

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