Abstract
In the present paper, the mixed-integer global optimization problems are considered. A novel deterministic algorithm for solving the problems of this class based on the information-statistical approach to solving the continuous global optimization problems has been proposed. The comparison of this algorithm with known analogs demonstrating the efficiency of the developed approach has been conducted. The stable operation of the algorithm was confirmed also by solving a series of several hundred mixed-integer global optimization problems.
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CITATION STYLE
Gergel, V., Barkalov, K., & Lebedev, I. (2019). A global optimization algorithm for non-convex mixed-integer problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11353 LNCS, pp. 78–81). Springer Verlag. https://doi.org/10.1007/978-3-030-05348-2_7
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