基于模糊预测性线性规划的矿山产能分配方案优化分析

Optimization analysis of mining capacity allocation scheme based on fuzzy predictive linear programming

针对传统矿山产能分配方案分析过程具有较为简单、不系统科学的弊端,将矿山能源,资源及人力条件作为模糊约束条件,以不同采区的单位矿石产量的消耗作为约束系数,构建综合模糊线性规划及灰色线性规划的模糊预测型线性规划模型,对矿山产能分配方案进行系统科学的分析。利用多种灰色预测理论经过精度比较与优选后对灰色系数进行白化,并利用模糊最优判决条件将模糊预测性线性规划模型转化为一般线性规划模型进行求解,进而得到矿山最优产能分配方案。经实例验证,该方法科学可行,能够实现矿山企业生产资料的科学配置和利润的最大化。

The traditional analysis process of mining capacity allocation scheme was simple, without system scientic analysis. Mining energy, resources and the human condition were taken as fuzzy constraints, consumption of units ore production for different mining areas was used as constraint coefficients, fuzzy predictive linear programming was built based on fuzzy linear programming and gray linear programming, and mining capacity allocation scheme system was scenically analyzed by fuzzy predictive linear programmings. A variety of gray prediction programming were used to whiten gray coefficients after accuracy compared and preferred, and fuzzy optimal decision was used to turn fuzzy linear programming model into linear programming model to achieve the optimal capacity allocation. It is proved that this model is scientific and feasible and the scientific configuration of means of production and the maximization of profits for mining enterprises can be achieved.