A New Updated Strategy Shuffled Frog Leaping Algorithm based on Gravitation Search Algorithm

DOI

10.2991/ic3me-15.2015.276How to use a DOI?

Keywords

Shuffled Frog Leaping Algorithm, Gravitational search algorithm, Optimizing Performance

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 1432
EP  - 1437
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.276
DO  - 10.2991/ic3me-15.2015.276
ID  - Sun2015/08
ER  -