Ecological operation of cascade hydropower reservoirs by elite-guide gravitational search algorithm with Lévy flight local search and mutation

2020 ◽  
Vol 581 ◽  
pp. 124425 ◽  
Author(s):  
Zhong-kai Feng ◽  
Shuai Liu ◽  
Wen-jing Niu ◽  
Shu-shan Li ◽  
Hui-jun Wu ◽  
...  
Keyword(s):  
Local Search ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Lévy Flight ◽  
Levy Flight ◽  
Gravitational Search ◽  
Hydropower Reservoirs

scholarly journals A gravitational search algorithm based on levy flight

2021 ◽  
Vol 1865 (4) ◽  
pp. 042006
Author(s):  
Jing Zhao ◽  
Haidong Zhu ◽  
Yinhua Hu ◽  
Enjun Hu ◽  
Baole Huang ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Lévy Flight ◽  
Levy Flight ◽  
Gravitational Search

scholarly journals Levy Flight and Chaos Theory Based Gravitational Search Algorithm for Global Optimization

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Performance Metrics ◽  
Chaotic Maps ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Lévy Flight ◽  
Step Size ◽  
Levy Flight ◽  
Statistical Measures ◽  
Engineering Design Problems ◽  
Gravitational Search

The Gravitational Search Algorithm (GSA) is one of the highly regarded population-based algorithms. It has been reported that GSA has a powerful global exploration capability but suffers from the limitations of getting stuck in local optima and slow convergence speed. In order to resolve the aforementioned issues, a modified version of GSA has been proposed based on levy flight distribution and chaotic maps (LCGSA). In LCGSA, the diversification is performed by utilizing the high step size value of levy flight distribution while exploitation is carried out by chaotic maps. The LCGSA is tested on well-known 23 classical benchmark functions. Moreover, it is also applied to three constrained engineering design problems. Furthermore, the analysis of results is performed through various performance metrics like statistical measures, convergence rate, and so on. Also, a signed Wilcoxon rank-sum test has also been conducted. The simulation results indicate that LCGSA provides better results as compared to standard GSA and most of the competing algorithms.

scholarly journals Self-Adaptive Gravitational Search Algorithm With a Modified Chaotic Local Search

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 17881-17895 ◽  
Author(s):  
Junkai Ji ◽  
Shangce Gao ◽  
Shuaiqun Wang ◽  
Yajiao Tang ◽  
Hang Yu ◽  
...  
Keyword(s):  
Local Search ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Gravitational Search ◽  
Self Adaptive

Analysis of Optimal Power Flow Using Gravitational Search Algorithm

2016 ◽  
Vol 3 (4) ◽  
pp. 1-11
Author(s):  
M. Lakshmikantha Reddy ◽  
◽  
M. Ramprasad Reddy ◽  
V.C. Veera Reddy ◽  
◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Power ◽  
Gravitational Search
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