Young’s double-slit experiment optimizer (YDSE)

Version 1.0.0 (11,4 ko) par Reda Mohamed
YDSE optimizer is a physics-based metaheuristic algorithm
219 téléchargements
Mise à jour 13 mars 2023

Afficher la licence

The YDSE optimizer is inspired by Young’s double-slit experiment, which is regarded as one of the most well-known classical physics experiments, revealing the wave nature of light. In YDSE optimizer, each fringe represents a possible solution in the population. Many concepts are modeled from the experiment, such as monochromatic light waves, Huygens’ principle, constructive and destructive interference, wave intensity, amplitude, and path difference. The YDSE optimizer strikes a balance between exploration and exploitation by selecting either a constructive interference or a destructive interference based on the order number of the fringe.
The performance of the YDSE optimizer is compared with another twelve metaheuristics using CEC 2014, CEC 2017, and CEC 2022. The benchmarks cover different unimodal, multimodal, hybrid, and composite test functions. Also, we consider ten constrained and unconstrained engineering optimization design problems. YDSE proved its superiority over the CEC 2014 and CEC 2017 winners, such as L-SHADE, LSHADE-cnEpSin, and LSHADE-SPACMA. The results and the statistical analysis demonstrated the outperformance of the proposed YDSE optimizer at a 95% confidence interval.
Main Paper:Abdel-Basset, M., El-Shahat, D., Jameel, M., & Abouhawwash, M. (2023). Young’s double-slit experiment optimizer: A novel metaheuristic optimization algorithm for global and constraint optimization problems. Computer Methods in Applied Mechanics and Engineering.‏ DOI:https://doi.org/10.1016/j.cma.2022.115652

Citation pour cette source

Reda Mohamed (2024). Young’s double-slit experiment optimizer (YDSE) (https://www.mathworks.com/matlabcentral/fileexchange/126205-young-s-double-slit-experiment-optimizer-ydse), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2022b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Tags Ajouter des tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Publié le Notes de version
1.0.0