基于GA的矿山企业动态生产经营参数优化

Parameters Optimization of Dynamic Production and Management for Mining Enterprise Based on GA

为最大化利用不可再生的矿产资源,实现矿山企业的矿石储量、开采品位、开采成本、价格四要素之间的动态联动与优化,采用基因算法求解矿山企业多目标生产经营参数优化。通过建立4个优化目标之间的联动求解模型,将影响多目标优化的要素作为遗传算法的初始染色体,并对基因算法运算规则进行重新定义,以求解矿山企业多目标生产经营参数优化,实现了矿山企业动态生产经营参数优化模型。运用该模型,可根据矿产品的价格变化确定盈亏品位界限、成本与价格比和储量可供情况,为保护、利用矿产资源提供科学手段。

To maximize the use of non-renewable mineral resources to achieve the ore reserves of mining enterprises,mining grade and cost,the price of dynamic linkage between the four elements and optimization,Genetic Algorithm（GA） is adopted to solve production and operation of mining enterprises multi-objective parameter optimization.Through the establishment of the four optimized solution model,will affect the elements of multi-objective optimization genetic algorithm as the initial chromosome,and genetic algorithms are re-defined to solve mine enterprise production and operation of multi-objective parameter optimization to achieve a dynamic production and operation of mining enterprises parameter optimization model.The use of this model,according to mineral price changes can be simple,quick and intuitive adjustment of mining costs to determine profit and loss limits of taste,cost and price ratio and the reserves available for the situation.