A New Updated Strategy Shuffled Frog Leaping Algorithm based on Gravitation Search Algorithm
Yuhong Sun, Wei Liu, Yueshan Xie, Wuji He, Hao Chen
Available Online August 2015.
- https://doi.org/10.2991/ic3me-15.2015.276How to use a DOI?
- Shuffled Frog Leaping Algorithm, Gravitational search algorithm, Optimizing Performance
- In dealing with the problem that basic SFLA neglect the information exchange between individuals and sub-population in searching optimal solution, this paper proposes a new improved SFLA based on update rule of the Gravitation Search Algorithm. Based on the ideal from gravitation algorithm, the new SFLA regards the frog as a material with real quality and there exists mutual effect between any two frogs, a new update rule is proposed in this paper, which is able to drive the whole population to the optimal solution by prompting the movement of the worst frog under the effect of the gravitation. The simulation results show that the improved SFLA takes full advantage of the information between the sub-population to improve solution accuracy and convergence rate, which has a better practical performance and optimized performance.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yuhong Sun AU - Wei Liu AU - Yueshan Xie AU - Wuji He AU - Hao Chen PY - 2015/08 DA - 2015/08 TI - A New Updated Strategy Shuffled Frog Leaping Algorithm based on Gravitation Search Algorithm BT - 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ic3me-15.2015.276 DO - https://doi.org/10.2991/ic3me-15.2015.276 ID - Sun2015/08 ER -