Economic dispatch using hybrid grey wolf optimizer
By T. Jayabarathi, T. Raghunathan, B. Adarsh, Ponnuthurai Nagaratnam Suganthan. 2016
324 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/2ae987a7164aa42acb4c0c5780df36f5efb6745d
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In Electrical and Electronic Engineering
- Mohammad-Hossein Nadimi-Shahraki
- Kusum Deep
- Parham Pahlavani
- Seyedali Mirjalili
- S. Mirjalili
- Hossam Faris
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- Shubham Kumar Gupta
Citations in the corpus
- Grey wolf optimizer: a review of recent variants and applications (2017, methodology): “In [41], the ELD problem is also addressed using a hybridized version of GWO.”
- An efficient modified grey wolf optimizer with Lévy flight for optimization tasks (2017, methodology): “In [39], the original GWO has been hybridized with mutation and crossover mechanisms to tackle the economic dispatch problems.”
- A novel Random Walk Grey Wolf Optimizer (2019, methodology): “[18] GWO has been hybridized with crossover and mutation to solve four problems of economic dispatch.”
- An improved grey wolf optimizer for solving engineering problems (2021, methodology): “Jayabarathi et al. (Jayabarathi et al., 2016) introduced HGWO to solve the economic dispatch problem by using the mutation and crossover operators in GWO.”
- Using a kernel extreme learning machine with grey wolf optimization to predict the displacement of step-like landslide (2019, background): “We report here a case study on the Baishuihe landslide, a typical step-like landslide in the Three Gorges Reservoir Area (TGRA) of China.”