Synergistic Fibroblast Optimization (SFO) is a stochastic population based global search algorithm which has been developed by the inspiration obtained from the intellectual behavior of fibroblast organisms present in the dermal wound healing process. Various characteristics of fibroblast include differentiation, proliferation, inflammation, migration, reorientation, alignment, ECM synthesis, collaborative, goal-oriented, interaction, regeneration, self adaptation and evolution are studied to design and develop a computational model of SFO algorithm. The goal of this SFO algorithm is to find a global optimum (minima or maxima) solution.
The algorithm and the architecture of this newly developed Nature inspired SFO algorithm has been given below for the perusal of researchers worldwide. The MATLAB code for this algorithm is also enclosed. 2 research papers presented and published in International forums have been listed out. Few more papers are yet to be published. I request those who are using the algorithm and code in their research to kindly cite the papers.
P Subashini (2023). Synergistic Fibroblast Optimization code (https://www.mathworks.com/matlabcentral/fileexchange/60027-synergistic-fibroblast-optimization-code), MATLAB Central File Exchange. Retrieved .
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Inspired by: optimization
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Zip file contains the code and description about SFO