UDC 004.852

INFORMATION AND ALGORITHMIC PRINCIPLES OF TASK PRIORITIZATION UNDER MULTICRITERIA UNCERTAINTY

Published in Scientific and analytical journal «Vestnik Saint-Petersburg university of State fire service of EMERCOM of Russia» · Volume 2025, Issue 3 · Pages 147–155 · Rubric: WORKS OF YOUNG SCIENTISTS
DOI: https://doi.org/10.61260/2218-130X-2025-3-147-155
Received: 25.06.2025 Accepted: 21.07.2025 Published: 20.10.2025 Language of publication: ru-RU
The paper addresses the task of prioritizing items in information systems operating under incomplete and changing data. It presents an analysis of existing methods (Analytic Hierarchy Process, Technique for Order of Preference by Similarity to Ideal Solution, heuristics, machine learning) and shows that none of them fully meet the requirements of robustness, adaptability, and interpretability. To address this, the authors propose a new model that automatically evaluates the importance of features, handles missing data, and provides understandable results. The model also adjusts priorities based on task dependencies. A numerical experiment confirms that the model remains stable even with significant data loss. The solution is applicable in help desk systems, project management, digital platforms, and real-time processing environments.
task prioritization, incomplete data, adaptive algorithm, information systems, interpretability, multicriteria analysis
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