Multiobjective Differential Evolution Based on Fuzzy Performance Feedback
This is the matlab code for FMDE. FMDE uses performance metric specifically hypervolume, spacing, and maximum spread to measure the state of the evolution process. The authors apply the fuzzy inference rules to these metrics in order to adjust the associate constrol parameters of a chosen mutation strategy used in this algorithm. Therefore, the authors can appropriately adjust the degree of exploration and exploitation through performance feedback.
The detail information of FMDE can be found in
[1] Jariyatantiwait, C. and Yen, G. G., "Fuzzy multiobjective differential evolution using performance metrics
feedback," Evolutionary Computation (CEC), 2014 IEEE Congress on, pp. 1959-1966, July, 2014.
[2] Jariyatantiwait, C., & Yen, G. G. (2014). Multiobjective Differential Evolution Based on Fuzzy Performance
Feedback. International Journal of Swarm Intelligence Research (IJSIR), 5(4) 45-64.
Cite As
Kaew (2024). Multiobjective Differential Evolution Based on Fuzzy Performance Feedback (https://www.mathworks.com/matlabcentral/fileexchange/52575-multiobjective-differential-evolution-based-on-fuzzy-performance-feedback), MATLAB Central File Exchange. Retrieved .
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Acknowledgements
Inspired by: NSGA - II: A multi-objective optimization algorithm
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Version | Published | Release Notes | |
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1.0.0.0 |