Specific Parameter-Free Global Optimization to Speed Up Setting and Avoid Factors Interactions

Year, pages: 2019, 265 - 290

Meta-heuristics utilizing numerous parameters are more complicated than meta-heuristics with a couple of parameters for various reasons. In essence, the effort expected to tune the strategy-particular parameters is far more prominent as the quantity of parameters increases and furthermore, complex algorithms are liable for the presence of further parameter interactions. Jaya meta-heuristic does not involve any strategy-specific parameters and is a one-stage technique. It has demonstrated its effectiveness compared to major types of meta-heuristics and it introduces various points of interest, such as its easy deployment and set-up in industrial applications and its low complexity to be studied. In this work, a new meta-heuristic, Enhanced Jaya (EJaya) is proposed to overcome the inconsistency of Jaya in diverse situations, introducing coherent attraction and repulsion movements and restrained intensity for flight. Comparative results of EJaya in a set of benchmark problems including statistical tests show that it is feasible to increase the accuracy, scalability and exploitation capability of Jaya while keeping its specific parameter-free feature. EJaya is especially suitable for a priori undefined characteristics optimization functions or applications where the set-up time of the optimization process is critical and parameters tuning and interactions must be avoided.

Reche, R., Prado, R., Galán, S., Expósito, J., Reyes, N. 2019. Specific Parameter-Free Global Optimization to Speed Up Setting and Avoid Factors Interactions. In Computing and Informatics, vol. 38, no.2, pp. 265-290. 1335-9150. DOI: https://doi.org/10.31577/cai_2019_2_265

Reche, R., Prado, R., Galán, S., Expósito, J., Reyes, N. (2019). Specific Parameter-Free Global Optimization to Speed Up Setting and Avoid Factors Interactions. Computing and Informatics, 38(2), 265-290. 1335-9150. DOI: https://doi.org/10.31577/cai_2019_2_265

Publisher: Ústav informatiky SAV