MATLAB code for the Adaptive Particularly Tunable Fuzzy PSO (APT-FPSO) algorithm, featuring adaptive fuzzy logic for dynamic parameter tuning to enhance optimization performance.
This repository features the Adaptive Particularly Tunable Fuzzy Particle Swarm Optimization (APT-FPSO) algorithm, an advanced variant of the standard Particle Swarm Optimization (PSO). Utilizing fuzzy logic, APT-FPSO adaptively tunes the learning coefficients for each particle at every iteration, enhancing the algorithm's balance between exploration and exploitation. The repository focuses on a single benchmark function, Griewangk, and demonstrates APT-FPSO’s effectiveness through detailed statistical analysis. This implementation is ideal for exploring the algorithm’s capabilities in complex optimization scenarios that require robust performance. For more detailed information, please read this paper. You can also find the PDF version of the paper in the repository.
- Four different versions of the APT-FPSO algorithm are provided with different rule-base structures.
- The repository focuses on a single benchmark function, Griewangk.
To run the main file for the project, use the following command in MATLAB:
pso_simulation_fit_fun_Griewangk_fl_4_8_20.m