Adaptive gbest-guided gravitational search algorithm

版本 1.1 (85.6 KB) 作者: Seyedali Mirjalili
A gbest-guided gravitational search algorithm
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更新时间 2018/5/22

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Adaptive Gbest-guided Gravitational Search Algorithm (GGSA) saves and utilizes the best solution obtained so far (gbest) as an accelerator towards the optimum during optimization.
Please note that this submission is the same as the original GSA algorithm (http://www.mathworks.com.au/matlabcentral/fileexchange/27756-gravitational-search-algorithm--gsa-), yet the only different component is the Move2.m, GGSA.m, and main.m files.
For more information please refer to the following papers:

1) S. Mirjalili, A. Lewis, Adaptive gbest-guided gravitational search algorithm, Neural Computing and Applications, in press, 2014, DOI: http://dx.doi.org/10.1007/s00521-014-1640-y

2) S. Mirjalili, G-G. Wang, L. S. Coelho, Binary optimization using hybrid particle swarm optimization and gravitational search algorithm, Neural Computing and Applications, in press, 2014, DOI: http://dx.doi.org/10.1007/s00521-014-1629-6

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引用格式

Seyedali Mirjalili (2025). Adaptive gbest-guided gravitational search algorithm (https://ww2.mathworks.cn/matlabcentral/fileexchange/47716-adaptive-gbest-guided-gravitational-search-algorithm), MATLAB Central File Exchange. 检索时间: .

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1.1

Links added:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF
This submission is now available as a Toolbox file in R2014b.

1.0.0.0