SOMA PARETO

SOMA codes are no longer updated on this MathWorks website. Please visit the author's GitHub for updates: https://github.com/diepquocbao
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Updated 7 Jan 2022

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We propose a new method named SOMA Pareto, in which the algorithm is divided into the Organization, Migration, and Update processes. The important key in the Organization process is the application of the Pareto Principle to select the Migrant and the Leader, increasing the performance of the algorithm. The adaptive PRT, Step, and PRTVector parameters are applied to enhance the ability to search for promising subspaces and then to focus on exploiting that subspaces.

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DiepQ., ZelinkaI. and DasS. 2019. Self-Organizing Migrating Algorithm Pareto. MENDEL. 25, 1 (Jun. 2019), 111-120. DOI:https://doi.org/10.13164/mendel.2019.1.111.

MATLAB Release Compatibility
Created with R2019a
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Version Published Release Notes
1.0.2

SOMA codes are no longer updated on this MathWorks website.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

1.0.1

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1.0.0