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Pryakhin V.N., Glaz R.A. Analysis and selection of the optimal method of industrial and agricultural waste disposal. Russian journal of resources, conservation and recycling. 2026; 13(1). Available at: https://resources.today/PDF/17INOR126.pdf (in Russian).

Analysis and selection of the optimal method of industrial and agricultural waste disposal

Pryakhin Vadim Nikolaevich
Dubna University, Dubna, Russia
E-mail: vpryahin@inbox.ru
RSCI: https://elibrary.ru/author_profile.asp?id=416286

Glaz Roman Alekseevich
Dubna University, Dubna, Russia
E-mail: Roma_glaz@inbox.ru
ORCID: https://orcid.org/0000-0003-3787-5321
RSCI: https://elibrary.ru/author_profile.asp?id=1169320

Abstract. This article presents a systematic analysis of the problem of selecting optimal methods for industrial and agricultural waste utilization as a complex multi-criteria decision-making task under uncertainty. The relevance of the study is determined by the diversity of waste types (electronic, electroplating, oil sludge, tannery waste, agricultural plastic, manure, crop residues), differences in their physicochemical properties and hazard classes, as well as the wide range of available processing technologies (mechanical, chemical, thermal, biochemical). Modern mathematical decision support methods are considered: hybrid models based on Cubic Fermatean Fuzzy Sets, which allow accounting for both point and interval expert estimates; Analytic Hierarchy Process (AHP) and SWARA methods for determining criteria weights; compromise ranking methods VIKOR and MARCOS. A comparative analysis of the efficiency of various waste processing technologies is performed: pyrolysis, gasification, anaerobic digestion for agro-industrial waste; mechanochemical activation, supercritical fluid extraction, waste stabilization for industrial waste; liquefaction and chemical recycling methods for agricultural plastic. A multi-criteria optimization methodology is proposed, considering environmental (greenhouse gas emissions, environmental impact), economic (capital and operating costs, payback period), technical (reliability, maturity, flexibility), and social criteria. Based on statistical data analysis for the period 2021–2025, industry development patterns are identified, and recommendations are formulated for selecting optimal technologies for different waste categories, considering regional specifics and uncertainty factors. A conceptual architecture of a decision support system is developed for decision-makers responsible for selecting utilization methods.

Keywords: system analysis; industrial waste; agricultural waste; multi-criteria decision making; fuzzy sets; optimization; utilization; circular economy

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