Articles | Volume 64
https://doi.org/10.5194/adgeo-64-23-2024
https://doi.org/10.5194/adgeo-64-23-2024
22 Aug 2024
 | 22 Aug 2024

An Efficient Surrogate-based Multi-objective Optimisation Framework with Novel Sampling Strategy for Sustainable Island Groundwater Management

Weijiang Yu, Domenico Baù, Alex S. Mayer, and Mohammadali Geranmehr

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Short summary
This study proposes an offline machine-learning (ML) algorithm that ranks candidate training points by scoring them based on their distance to the closest training point and on the local gradient of the surrogate estimate and then choosing the highest-rank point. The effectiveness of this method is confirmed in developing surrogates to solve a two-objective groundwater pumping optimization problem formulated on a three-dimensional island aquifer.