Feat: Add Chef-Based Optimization Algorithm (CBOA) implementation #272
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Description This PR adds the Chef-Based Optimization Algorithm (CBOA) to the human_based group. Reference Beskirli, A. (2025). Improved Chef-Based Optimization Algorithm with Chaos-Based Fitness Distance Balance for Frequency-Constrained Truss Structures. GU J Sci, Part A, 12(2), 392-416. DOI: https://doi.org/10.54287/gujsa.1667182 Changes - Added CBOA.py to mealpy/human_based/ - Added OriginalCBOA class - original implementation based on the paper Parameters - epoch (int): Maximum number of iterations, default = 250 - pop_size (int): Number of population size, default = 50
Imported CBOA module from human_based package to the main mealpy namespace. This allows users to access the algorithm via 'from mealpy import CBOA'.
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Closes # N/A
📑 Description
This PR introduces the Chef-Based Optimization Algorithm (CBOA) to the
human_basedmodule.The implementation follows the logic and experimental setup described in the referenced paper.
Reference:
Beskirli, A. (2025). Improved Chef-Based Optimization Algorithm with Chaos-Based Fitness Distance Balance for Frequency-Constrained Truss Structures. GU J Sci, Part A, 12(2), 392-416.
DOI: https://doi.org/10.54287/gujsa.1667182
Key Changes:
mealpy/human_based/CBOA.pyOriginalCBOAclass with dynamic chef selection logic.mealpy/human_based/__init__.pyto expose the new class.✅ Checks
ℹ Additional Information
Default parameters have been configured based on the experimental setup in Beskirli (2025):
epoch: 250pop_size: 50