APPLICATION OF MACHINE LEARNING METHODS TO THE PROBLEM OF AGRICULTURAL FACILITY LOCATION
DOI:
https://doi.org/10.47390/ts-v3i11y2025No3Keywords:
multicriteria models, decision-making, artificial intelligence, Pareto frontier, HyperNetwork, optimal solution.Abstract
This article examines the application of artificial intelligence methods to solving problems that arise when searching for solutions to multicriteria models used for analyzing and optimizing processes in various economic sectors. The study applies the Pareto Front Learning (PFL) method and evaluates its effectiveness in identifying Pareto-optimal solutions in multicriteria mathematical models, achieving their rapid and accurate approximation, and addressing resource allocation imbalances in agricultural facility location tasks. The results demonstrate that the practical implementation of this method enables the generation of high-quality solutions that closely approximate the true Pareto frontier.
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