Mexican Axolotl Optimization: a novel bioinspired heuristic

Novel bioinspired algorithm for numeric optimization: the Mexican Axolotl Optimization algorithm

The purpose of this research is to design a novel bioinspired algorithm for numeric optimization: the Mexican Axolotl Optimization algorithm. The effectiveness of our proposal was compared against seven optimization algorithms (artificial bee colony, cuckoo search, dragonfly algorithm, differential evolution, firefly algorithm, fitness dependent optimizer, and whale optimization algorithm) when applied over four sets of benchmark functions (unimodal, multimodal, composite and competition functions). The statistical analysis shows the ability of Mexican Axolotl Optimization algorithm of obtained very good optimization results in all experiments, except for composite functions where the Mexican Axolotl Optimization algorithm exhibits an average performance.

Villuendas-Rey, Y., Velázquez-Rodríguez, J. L., Alanis-Tamez, M. D., Moreno-Ibarra, M. A., & Yáñez-Márquez, C. (2021). Mexican Axolotl Optimization: A Novel Bioinspired Heuristic. Mathematics, 9(7), 781.

https://www.mdpi.com/2227-7390/9/7/781

Authors

* Yenny Villuendas-Rey

* José Luis Velázquez-Rodríguez

* Mariana D. Alanís Tamez

* Marco Antonio Moreno Ibarra

* Cornelio Yáñez Márquez