ADAPTIVE MODELING OF MINING SCHEDULE USING GENETIC ALGORITHM IN A DYNAMIC ENVIRONMENT
ДИНАМИКАЛЫҚ БАСҚАРУ ОРТАСЫНДА ГЕНЕТИКАЛЫҚ АЛГОРИТМ АРҚЫЛЫ ТАУ-КЕН РЕЖИМІН БЕЙІМДЕУ
АДАПТИВНОЕ МОДЕЛИРОВАНИЕ РЕЖИМА ГОРНЫХ РАБОТ ПОСРЕДСТВОМ ГЕНЕТИЧЕСКОГО АЛГОРИТМА В ДИНАМИЧНОЙ СРЕДЕ ХОЗЯЙСТВОВАНИЯ
Hryhoriev Y. Lutsenko S. Hryhoriev I. Kuttybayev A. Kuantayev N.
January-February 2026National Academy of Sciences of the Republic of Kazakhstan
News of the National Academy of Sciences of the Republic of Kazakhstan, Series of Geology and Technical Sciences
2026#2026Issue 1120 - 134 pp.
The operation of large mining clusters faces significant challenges, as long-term planning is often based on constant environmental conditions, ignoring uncertainties in the economic environment, geological uncertainty, and the mutual influence of enterprises. However, the current realities of the global market and the challenges of the industrial crisis require consideration of dynamic conditions, such as price and demand fluctuations, during mining operations. This study proposes a method for multi-factor optimization of mining operations based on a genetic algorithm. The methodology involves the mathematical formalization of a mining cluster system combining open pit mines and industrial deposits, using an evolutionary approach to solving nonlinear optimization problems that take into account ore quality and mining costs. The study identified optimal parameters for the optimization algorithm - specifically, a crossover value of 0.7-0.8 and a mutation probability of 5% - to ensure the accuracy of design decisions and prevent optimization from drifting toward local minima. The proposed model determines annual production blocks, storage volumes, and processing of man-made deposits, enabling dynamic adjustments to cutoff ore grade values to minimize overall costs. Unlike traditional deterministic approaches, the proposed methodology provides flexibility in planning, enabling long-term reductions in production and storage costs while maintaining stable ore quality. The results obtained can be used by engineering design organizations for adaptive, dynamic long-term design of mining facilities and regional clusters, as well as for improving the specialized software used for this purpose.
adaptive design , mathematical modeling , open-pit , ore quality , regional mining cluster , тechnogenic deposits
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Department of Open-Pit Mining, Kryvyi Rih National University, Kryvyi Rih, Ukraine
Mining Department, LLC Technical University Metinvest polytechnic, Zaporizhzhia, Ukraine
Department Mining, Satbayev University, Almaty, Kazakhstan
Department of Open-Pit Mining
Mining Department
Department Mining
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026