Research On Optimizing The Economical Technical Parameter And Strategy For Business On Coexistence Multi-metal Mines

The world mineral development is undergoing a transition from extensive form to fine digital form, more and more mine production enterprises are gaining a lasting competitive advantage through internal production technical indicator optimization. With the rapid development of China's economy, GDP per capita is at a rising dependence on mineral resources. Moreover, the comprehensive utilization of mineral resources in China is ralatively low, and there is a certain gap between us and foreign counterparts in the fine mineral development level and ability, leading to a relatively low economic benefits of mineral development and a reducing capacity for sustainable supply of mineral resources, which has a serious effect on our sustainable development strategy for natural resources. This paper combines the research needs of national major issues, aiming at the forefront of mining development and management, has carried out researches for Chenzhou Mining Corporation about the optimization strategies of key indicators of production technology in mining enterprises. The main work in this paper is as the following.1):In allusion to the determination of the mineral products'cost amd market price, this paper discusses the complex linkage relationships among the mineral industrial grade, ore reserves, mining dilution rate, mining lose, recovery rates and smelting recovery. On the basis of corresponding improvement in particle swarm optimization algorithm(PSO), we carried out multi-objective optimization of multiple metal coexistence industrial grade index. The results show that the algorithm can be optimized to achieve extended life of mining enterprises, full use of resources and economic optimum, providing a new idea for the optimization of multiple metal coexistence industrial grade indexes.2):In allusion to the lacking of price and cost in PSO algorithm. This paper discusses the use of genetic algorithms (GA) to propose a new method to solve multi-objective production technology of mining enterprises optimization. Through the establishment of linkage solving model of ore reserves, mining grade, cost and price, we can calculate the production cost, determine profit and loss grade boundaries, the cost and price ratio and the reserves situation in accordance with changes in mineral prices, providing a scientific means for the dynamic management of reserves and grade, so that mineral mining enterprises can achieve sicence mine allocation, adopting both rich and poor, and improve resource utilization.3):In terms of determined industrial grade, this paper studies the complex nonlinear problems of dynamic mine allocation optimization, adopting an improved particle swarm algorithm to solve the problem of mining enterprises'dynamic mine allocation, that is, the ore particle is represented by a block, and the mineral block exploit is represented by 0 or 1, and then re-define the computing and the flight rule for PSO particles under constraint condition, and finally realized the PSO algorithm for mine allocation optimization. By the comparasion with actual production in 2009, the optimization results suggested that this algorithm can improve business efficiency significantly with almost unchanged const.4):In allusion to the lacking of consideration of long-term benefits of mining enterprises in previous dynamic mine allocation, proposing a several-rounds-PSO algorithm to solve the dynamic mine allocation in long term. First of all, delineating recoverable ore block according to mining conditions, and giveing the price trend forecast results as the algorithm input conditions. Then, through the PSO operator to determine the dynamic mine allocation program in each round, and the long-term dynamic optimization result is the result after several-rounds PSO algorithm. Through the calculation of actual data show, the effectiveness of the algorithm is proved.5):Mineral resources evaluation is an important basis of macroeconomic policy-making for mining enterprises, which involves a large number of production technical indicators, while there exists complex nonlinear relationship among them, resulting in challenges for rapid and accurate evaluation of mineral resources. This paper built a kind of resource assessment with nugget cumulative method, instead of traditional extensive calculation, to assess the total economic value of mineral resources. By using BP neural network to determine the impact evaluation of the intractable factors, that is, recovery rates, and deploy curve fitting to determine the dilution rate and loss rate of mines buried in different depth. Eventually, the mineral resource evaluation system is realized, and its effectiveness is proved through the calculation of actual data.The proposed optimazation of production technical indicators in this paper is an improvement of traditional technology assessment and it is a good guide for the optimazation of multiple metal coexistence industrial grade indexes. The new optimazation strategy proposed in this paper has been partly applied in ChenZhou mining enterprise, which achieves better actual results.