Data and code for: Simulation–optimization framework for robust managed aquifer recharge operation under hydrogeological uncertainty
Description
This dataset contains the source code, configuration files, model problem definitions, utility functions, optimization results, and Monte Carlo uncertainty-analysis results supporting the findings presented in the associated research article. The repository provides the complete computational framework used to perform the multi-objective optimization and uncertainty analysis described in the article. The optimization framework includes the implemented evolutionary and local-search algorithms, problem formulations, objective functions, constraints, and supporting utilities. Monte Carlo simulations are also provided to quantify uncertainty in the optimized solutions. The repository is organized as follows: main.py – Main script for configuring and executing the optimization and uncertainty-analysis workflow. config.py – Model, optimization, simulation, and analysis settings. Algorithms/ – Implementations of the optimization algorithms and associated procedures. problems/ – Problem definitions, objective functions, decision variables, constraints, and model-related components. utils/ – Supporting functions for model execution results/ – Optimization and Monte Carlo results used for the analyses presented in the article. requirements.txt – Python packages and dependencies required to run the code. README.txt – Instructions for installation, configuration, execution. The Monte Carlo results include simulations conducted with different numbers of realizations to assess the stability of the uncertainty estimates. These results support the selection of the number of Monte Carlo realizations used in the study. The files are provided to facilitate transparency, reproducibility, and further application or extension of the proposed optimization and uncertainty-analysis framework.