The niched pareto genetic algorithm 2 applied to the design of groundwater remediation systems
Document Type
Conference Proceeding
Publication Date
7-6-2001
Department
Department of Geological and Mining Engineering and Sciences
Abstract
We present an evolutionary approach to a difficult, multiobjective problem in groundwater quality management: how to pump-and-treat (PAT) contaminated groundwater to remove the most contaminant at the least cost. Although evolutionary multiobjective (EMO) techniques have been applied successfully to monitoring of groundwater quality and to containment of contaminated groundwater, our work is a first attempt to apply EMO to the long-term (ten year) remediation of contaminated water. We apply an improved version of the Niched Pareto GA (NPGA 2) to determine the pumping rates for up to fifteen fixed-location wells. The NPGA2 uses Pareto-rank-based tournament selection and criteria-space niching to find nondominated frontiers. With 15 well locations, the niched Pareto genetic algorithm is demonstrated to outperform both a single objective genetic algorithm (SGA) and enumerated random search (ERS) by generating a better tradeoff curve.
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Recommended Citation
Erickson, M.,
Mayer, A.,
&
Horn, J.
(2001).
The niched pareto genetic algorithm 2 applied to the design of groundwater remediation systems.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
1993, 681-695.
http://doi.org/10.1007/3-540-44719-9_48
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/4008