Self-organizing migrating algorithm with clustering-aided migration and adaptive perturbation vector control

Abstract

The paper proposes the Self-organizing Migrating Algorithm with CLustering-aided migration and adaptive Perturbation vector control (SOMA-CLP). The SOMA-CLP is the next iteration of the SOMA-CL algorithm, further enhanced by the linear adaptation of the prt control parameter used to generate a perturbation vector. The latest CEC 2021 benchmark set on a single objective bound-constrained optimization was used for the performance measurement of the improved variant. The proposed algorithm SOMA-CLP results were compared and tested for statistical significance against four other SOMA variants.