MinCentre: using clustering in global optimisation
by Vasileios Charilogis; Ioannis G. Tsoulos
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 11, No. 1, 2022

Abstract: A common problem that arises in many scientific fields is locating the global minimum of a multi-modal function. A novel clustering technique that tackles this problem is introduced here. The proposed method creates clusters from uniform samples of the objective function with the usage of the K-means clustering technique. For every cluster a centre is created. Finally, a simple rejection procedure is applied to the created clusters in order to remove clusters that are close to others. The proposed method is tested on a series of well-known optimisation problems from the relevant literature and the results are reported and compared against the simple multi-start global optimisation method.

Online publication date: Fri, 10-Jun-2022

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