In this paper, a new mechanism for detecting population stagnation based on the analysis of the local improvement of the evaluation function and the infinite impulse response filter is proposed. The purpose of this mechanism is to improve the population stagnation detection capability for various optimization scenarios, and thus to improve multi-population-based algorithms (MPBAs) performance. In addition, various other approaches have been proposed to eliminate stagnation, including approaches aimed at both improving performance and reducing the complexity of the algorithms. The developed methods were tested, among the others, for various migration topologies and various MPBAs, including the MNIA algorithm, which allows the use of many different base algorithms and thus eliminates the need to select the population-based algorithm for a given simulation problem. The simulations were performed for typical benchmark functions and control problems. The obtained results confirm the validity of the developed method.

A NEW APPROACH TO DETECTING AND PREVENTING POPULATIONS STAGNATION THROUGH DYNAMIC CHANGES IN MULTI-POPULATION-BASED ALGORITHMS / Lapa, K.; Rutkowska, D.; Byrski, A.; Napoli, C.. - In: JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH. - ISSN 2083-2567. - 13:4(2023), pp. 289-306. [10.2478/jaiscr-2023-0020]

A NEW APPROACH TO DETECTING AND PREVENTING POPULATIONS STAGNATION THROUGH DYNAMIC CHANGES IN MULTI-POPULATION-BASED ALGORITHMS

Napoli C.
Ultimo
Supervision
2023

Abstract

In this paper, a new mechanism for detecting population stagnation based on the analysis of the local improvement of the evaluation function and the infinite impulse response filter is proposed. The purpose of this mechanism is to improve the population stagnation detection capability for various optimization scenarios, and thus to improve multi-population-based algorithms (MPBAs) performance. In addition, various other approaches have been proposed to eliminate stagnation, including approaches aimed at both improving performance and reducing the complexity of the algorithms. The developed methods were tested, among the others, for various migration topologies and various MPBAs, including the MNIA algorithm, which allows the use of many different base algorithms and thus eliminates the need to select the population-based algorithm for a given simulation problem. The simulations were performed for typical benchmark functions and control problems. The obtained results confirm the validity of the developed method.
2023
migration topologies; multi-population-based algorithms; population stagnation
01 Pubblicazione su rivista::01a Articolo in rivista
A NEW APPROACH TO DETECTING AND PREVENTING POPULATIONS STAGNATION THROUGH DYNAMIC CHANGES IN MULTI-POPULATION-BASED ALGORITHMS / Lapa, K.; Rutkowska, D.; Byrski, A.; Napoli, C.. - In: JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH. - ISSN 2083-2567. - 13:4(2023), pp. 289-306. [10.2478/jaiscr-2023-0020]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1692302
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