Abstract
Differential evolution (DE) is a simple yet effective metaheuristic specially suited for real-parameter optimization. The most advanced DE variants take into account the feedback obtained in the self-optimization process to modify their internal parameters and components dynamically. In recent years, some controversies have arisen regarding the adaptive schemes that incorporate feedback from the search process to guide the adaptation of the mutation scale factor. Some researchers have claimed that no significant benefits are obtained with these kinds of schemes. However, other studies have shown that they are highly effective. In this paper, we show that there is a relationship between the effectiveness of these adaptive schemes and the balance between exploration and exploitation induced by the trial vector generation strategy considered. State-of-the-art adaptive schemes are not useful for the trial vector generation strategies with the highest levels of exploration, which in fact seems to be the reason behind the controversies of recent years.
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Acknowledgments
The second author is also affiliated with the UMI LAFMIA 3175 CNRS at CINVESTAV-IPN. He also acknowledges the financial support from CONACyT project no. 103570. This work was also funded in part by the ec (FEDER) and the Spanish Ministry of Science and Innovation as part of the ‘Plan Nacional de i+d+i’, with contract number tin2011-25448. The work of Eduardo Segredo was funded by grant fpu-ap2009-0457.
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Segura, C., Coello Coello, C.A., Segredo, E. et al. On the adaptation of the mutation scale factor in differential evolution. Optim Lett 9, 189–198 (2015). https://doi.org/10.1007/s11590-014-0723-0
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DOI: https://doi.org/10.1007/s11590-014-0723-0