Inverted generational distance is a widely used indicator for evaluating many-objective optimisation algorithms. In the past several years, numerous researchers have paid much attention to the improvement of many-obje...
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Inverted generational distance is a widely used indicator for evaluating many-objective optimisation algorithms. In the past several years, numerous researchers have paid much attention to the improvement of many-objective optimisation algorithms, while few researchers have mathematically analysed inverted generational distance. In this paper, we present detailed mathematical analyses of inverted generational distance, and then reveal the relation between generational distance and inverted generational distance. The conclusion is drawn that convergence plays different roles in different stages. Experimental results on seven many-objective benchmark problems verify our analyses.
Load frequency control is among the most important control tasks in power systems operation. many researchers have focused on tuning the load frequency controllers using single-objective evolutionary algorithms. To av...
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Load frequency control is among the most important control tasks in power systems operation. many researchers have focused on tuning the load frequency controllers using single-objective evolutionary algorithms. To avoid the drawbacks of single-objectiveoptimisationalgorithms, in this paper, tuning the load frequency controllers is modelled as a many-objective (MO) minimization problem. This MO optimisation problem is solved using an MO optimisationalgorithm with clustering-based selection. Considering the maximum value of each objective among the non-dominated solutions found by the MO optimisationalgorithm, the worst solution is determined. To select one of the obtained non-dominated solutions as the controllers' parameters, a strategy based on the maximum distance from the worst solution is proposed. In order to measure the effectiveness of the proposed MO technique against several recently proposed single-objectiveoptimisationalgorithms, for tuning load frequency controllers, comparative simulation studies are carried out on two different test systems. Simulation results show that, in terms of different performance indices, the controllers designed by the proposed MO method are far superior to the controllers designed with the single-objectiveoptimisationalgorithms. Also, the presented results confirm the robustness of the controllers designed by the proposed method in case of power system parameters variations.
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