ADAPTIVE OPTIMIZATION OF THE MINING SCHEDULE OF THE MINING CLUSTER USING A HEURISTIC MULTI-CRITERION ALGORITHM

Abstract

The article considers the scientific and technical foundations of the use of special mobile crushing and reloading devices as a key element of adaptive transport and technological systems of open-pit mining. The initial premise of the study is the need to increase the flexibility and stability of the functioning of excavator-automobile complexes in the complex mining-geological and technical and economic conditions of modern open-pits. A critical analysis of the development of intra-pit crushing and conveyor transport systems has been carried out, which has shown the limited adaptability of classical schemes to dynamic changes in production parameters. A concept for the introduction of mobile crushing and reloading units that combine the functions of buffer accumulation, primary crushing and reloading of the mining mass has been proposed. Methodologically, the study is based on a complex of general analytical, mining engineering and calculation methods, which allowed assessing the impact of the introduction of special mobile crushing and reloading devices on the productivity, energy efficiency and organizational stability of the complex. Comparative modeling of two variants of the excavator-automobile complex operation – basic and using a mobile loader – confirmed that the integration of these devices provides an increase in the utilization rate of excavators, a decrease in dump truck downtime and the possibility of optimizing the structure of the equipment fleet without loss of productivity. The practical result is to create prerequisites for the formation of adaptive schemes of open-pit mining operations, capable of flexibly responding to changes in the geometry of the side, ore body parameters and market conditions. The results obtained determine the direction of further research related to the development of algorithms for optimal spatial movement of the considered technical means and their integration into adaptive control systems for mining clusters.