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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.
Cite As
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.
General Information
- Version 1.0.2 (2.8 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
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| 1.0.2 | SOMA codes are no longer updated on this MathWorks website.
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| 1.0.1 | Add citation |
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| 1.0.0 |
