Nature has been observed and studied by researchers in the development of new optimization algorithms including the black hole (BH) algorithm. Variety of fundamental modification has been done mainly to enhance the exploration and exploitation capability of BH, which are important in optimization process. Among others, the BH has been modified by the inclusion of a white hole (WH) operator, which is also inspired by nature. The WH contributes toward the exploration of BH. In order to proof this, an experiment is conducted using 30 benchmark functions from the CEC20214 and the diversity curves of the BHWH and BH algorithm are presented and analyzed. Comparison of the diversity curve of BHWH with the diversity curve of BH only has proven that the introduction of WH operator is able to improve the exploration of BH by increasing the diversity and slowing the diversity convergence.

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