Metallurgical companies are currently facing an unstable market for iron ore and fuel/energy, which means that it is important to optimize the distribution of raw materials across multiple blast furnaces and determine the optimum composition of the blast-furnace charge for each furnace. Our analysis of current mathematical modeling approaches for determining the optimum distribution of iron-ore raw material across multiple blast furnaces indicated that the most promising approach involves full-scale modeling and the concept of perturbed object trajectories relative to a reference trajectory. The paper describes algorithm design, mathematical tools, and software for a system to determine the optimum distribution of raw materials and fuel/energy resources across multiple blast furnaces. The optimum raw-material resource distribution scheme implemented in the blast-furnace management system must support integration of the physical and chemical laws governing basic control-target and translator-model processes. The problem was solved by assuming small deviations of parameters from baseline conditions for the perturbed trajectory relative to a reference trajectory. We illustrate the blast-furnace operations planning capabilities of this software and methodology with respect to the cast-iron smelting process and improvement of performance statistics using the Magnitogorsk Metallurgical Complex PJSC (MMC PJSC) as an example.

中文翻译：

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多个高炉中原材料和燃料/能源资源的最佳分配

冶金公司目前面临着铁矿石和燃料/能源市场不稳定的局面，这意味着优化原材料在多个高炉中的分布并确定每个高炉的最佳高炉炉料组成非常重要。我们对当前用于确定铁矿石原材料在多个高炉中的最佳分布的数学建模方法的分析表明，最有前途的方法涉及全尺寸建模和相对于参考轨迹的扰动对象轨迹的概念。该论文描述了一个系统的算法设计、数学工具和软件，以确定原材料和燃料/能源在多个高炉中的最佳分配。在高炉管理系统中实施的最佳原材料资源分配方案必须支持控制基本控制目标和转换器模型过程的物理和化学规律的集成。该问题通过假设扰动轨迹相对于参考轨迹的基线条件的参数有很小的偏差来解决。我们以马格尼托哥尔斯克冶金联合体 PJSC (MMC PJSC) 为例，说明了该软件和方法在铸铁冶炼过程和性能统计改进方面的高炉操作规划功能。该问题通过假设扰动轨迹相对于参考轨迹的基线条件的参数有很小的偏差来解决。我们以马格尼托哥尔斯克冶金联合体 PJSC (MMC PJSC) 为例，说明了该软件和方法在铸铁冶炼过程和性能统计改进方面的高炉操作规划功能。该问题通过假设扰动轨迹相对于参考轨迹的基线条件的参数有很小的偏差来解决。我们以马格尼托哥尔斯克冶金联合体 PJSC (MMC PJSC) 为例，说明了该软件和方法在铸铁冶炼过程和性能统计改进方面的高炉操作规划功能。