Advanced Mathematical Models & Applications

Global optimization-based model for solving the data clustering problem depends on the type of the objective function. The existing model uses an exponential term in its objective function which apparently has a negative effect on the computational performance. This paper attempts to overcome the shortcomings experienced by the current model by initiating a new general form of the global optimization model. Computational performances of the proposed model is measured through the data clustering simulation. Three indicators, including CPU time, number of function evaluations, and number of iterations, are evaluated. Our new optimization model is then applied to earthquake investigation using Indonesian seismic data during 2022 and is compared to the existing model in order to evaluate the effectiveness and the predominance of our proposed model in discovering locations with various seismic activities.