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Online Selective Evolutionary Hyperheuristic for Large Scale Economic Load Dispatch Problem

机译:大规模经济负荷分配问题的在线选择性进化超启发式

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The economic load dispatch (ELD) problem is known as a hard optimization problem in the field of power system planning and control. Evolutionary algorithms (EAs) have demonstrated high performance in solving ELD problems with the number of power generator up to 40, but they lose their efficiency with high dimensionalities. In this study, we have proposed and have estimated the performance of a selective hyperheuristic for the online synthesis of an optimization algorithm based on large-scale optimization approaches.
机译:经济负荷分配(ELD)问题在电力系统规划和控制领域中被称为硬优化问题。进化算法(EA)在解决多达40台发电机的ELD问题方面已显示出高性能,但是随着高维数的增加,它们失去了效率。在这项研究中,我们提出并估计了基于大规模优化方法的在线优化算法的选择性超启发式算法的性能。

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