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An Improved Plant-wide Hierarchical Optimization Method Based on Technical Indices Decomposition

机译:一种改进的基于技术指标分解的植物范围的分层优化方法

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Basing on the minimum material consumption models, the plant-wide hierarchical optimization method has been successful in determining technical indices and manipulated variables by solving a two-level optimization problem, including the procedure-level optimization and the process-level optimization. However, the performance of the method will deteriorate if there are numerous technical indices and coupling relationship between them in the procedure-level optimization problem. To address this problem efficiently, this paper presents an improved plant-wide hierarchical optimization method based on technical indices decomposition. In the method, the procedure-level optimization problem is decomposed into several easier solvable sub-problems based on technical indices grouping. Two metrics are defined to measure whether the technical indices is divided into groups or separate. Then, the global optimum of procedure-level optimization problem is found by successively solving the sub-problems. Finally, the presented optimization method is applied to the hydrometallurgy process of a gold smelter. The results verify the effectiveness of this method.
机译:基于最小材料消耗模型,省级的分层优化方法已经成功地通过解决了两级优化问题来确定了技术指标和操纵变量,包括过程级优化和过程级优化。然而,如果在过程级优化问题中,如果在过程级优化问题之间存在许多技术指标和耦合关系,则该方法的性能将恶化。为了有效解决这个问题,本文提出了一种基于技术指标分解的植物范围的分层优化方法。在该方法中,过程级优化问题基于技术索引分组分解成几种更轻松的可溶性子问题。定义了两个度量标准,以衡量技术指标是否分为组或分开。然后,通过连续解决子问题,找到了过程级优化问题的全局最优。最后,呈现的优化方法应用于金色冶炼厂的氢晶冶金过程。结果验证了这种方法的有效性。

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