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This paper presents an enhanced group search optimizer (GSO), group search optimizer with intraspecific competition and lévy walk (GSOICLW), to solve the optimal power flow (OPF) problem. GSOICLW s a more biologically realistic algorithm and performs better balance between global and local searching than GSO n hat intraspecific competition IC) and lévy walk (LW) are introduced o GSO. GSOICLW is tested...
This paper presents a new algorithm, Function Optimisation by Reinforcement Learning (FORL), to solve large-scale and complex function optimisation problems, in particular for those in a high-dimensional space. FORL undertakes the dimensional search in sequence, in contrast to evolutionary algorithms (EAs) which are based on the population-based search, and has the ability of memory of history incorporated...
Optimal Power Flow (OPF) is an effective tool for dispatch planning of power systems, and the algorithms aiming to solve the OPF have been widely studied. Among these algorithms, the Evolutionary Algorithms (EAs) are a popular type, which have been investigated. However, EAs are also notorious for the intensive computation caused by a large amount of evaluations of the objective function required...
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