The iSOMA

SOMA codes are no longer updated on this MathWorks website. Please visit the author's GitHub for updates: https://github.com/diepquocbao

This algorithm is programmed according to the descriptions in the article:

Link of the article:

https://www.sciencedirect.com/science/article/pii/S1568494621010851

Please cite the article if you refer to them, as follows:

Diep, Quoc Bao, Thanh Cong Truong, Swagatam Das, and Ivan Zelinka. "Self-Organizing Migrating Algorithm with narrowing search space strategy for robot path planning." Applied Soft Computing (2021), doi: https://doi.org/10.1016/j.asoc.2021.108270

OR:

@article{DIEP2021108270,

title = {Self-Organizing Migrating Algorithm with narrowing search space strategy for robot path planning},

journal = {Applied Soft Computing},

pages = {108270},

year = {2021},

issn = {1568-4946},

doi = {https://doi.org/10.1016/j.asoc.2021.108270},

url = {https://www.sciencedirect.com/science/article/pii/S1568494621010851},

author = {Quoc Bao Diep and Thanh Cong Truong and Swagatam Das and Ivan Zelinka}

}

The control parameters PopSize, N_jump, m, n, and k are closely related

and greatly affect the performance of the algorithm. Please refer to the

above paper to use the correct control parameters.

The iSOMA will be adjusted in the near future for faster execution (using Vectorization)

and rebuilt to address more complex computational functions (a few minutes to complete one FEs)

that take advantage of Parallel Computing Toolbox to execute on supercomputer.

The iSOMA is also available in Matlab, python, and C# version, alongside some other versions like SOMA T3A and SOMA Pareto.

If you encounter any problems in executing these codes, please do not hesitate to contact:

Dr. Quoc Bao Diep ([e-mail].)