Optimization of a groundwater quality campaign utilizing the NSGA-II with preference ordering algorithm, contamination risk maps and well availability.

Abstract

This work focused in selecting 70 wells to conduct a groundwater quality sampling campaign. The wells were selected using 4 objectis: contamination risk of NT and CT, the coverage area and the wells which are publicly accessible. A Multiobjective Optimization Problem was defined to obtain the possible selections, and the Nondominated Sorting Genetic Algorithm II with Preference Ordering was implemented to solve it. The proposed solutions allowed the selection of 70 wells, 86% correspond to the wells which are publicly accessible, 70% of the wells are located in places with the high indices of contamination risk and cover 74% of the study area.