Usage of Selected Swarm Intelligence Algorithms for Piecewise Linearization

Nicole Škorupová, Petr Raunigr and Petr Bujok
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Nicole Škorupová: CE IT4Innovations–IRAFM, University of Ostrava, 70103 Ostrava, Czech Republic
Petr Raunigr: Department of Informatics and Computers, University of Ostrava, 30. dubna 22, 70103 Ostrava, Czech Republic
Petr Bujok: Department of Informatics and Computers, University of Ostrava, 30. dubna 22, 70103 Ostrava, Czech Republic

Mathematics, 2022, vol. 10, issue 5, 1-24

Abstract: The paper introduces a new approach to enhance optimization algorithms when solving the piecewise linearization problem of a given function. Eight swarm intelligence algorithms were selected to be experimentally compared. The problem is represented by the calculation of the distance between the original function and the estimation from the piecewise linear function. Here, the piecewise linearization of 2D functions is studied. Each of the employed swarm intelligence algorithms is enhanced by a newly proposed automatic detection of the number of piecewise linear parts that determine the discretization points to calculate the distance between the original and piecewise linear function. The original algorithms and their enhanced variants are compared on several examples of piecewise linearization problems. The results show that the enhanced approach performs sufficiently better when it creates a very promising approximation of functions. Moreover, the degree of precision is slightly decreased by the focus on the speed of the optimization process.

Keywords: swarm intelligence algorithms; piecewise linearization; optimization; parameter tuning; approximation; experimental comparison (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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