Multi-armed Bandit-Based Metaheuristic Operator Selection: The Pendulum Algorithm Binarization Case

Pablo Ábrego-Calderón, Broderick Crawford, Ricardo Soto, Eduardo Rodriguez-Tello, Felipe Cisternas-Caneo, Eric Monfroy, Giovanni Giachetti

Producción científica: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Multi-armed bandit (MAB) is a well-known reinforcement learning algorithm that has shown outstanding performance for recommendation systems and other areas. On the other hand, metaheuristic algorithms have gained much popularity due to their great performance in solving complex problems with endless search spaces. Pendulum Search Algorithm (PSA) is a recently created metaheuristic inspired by the harmonic motion of a pendulum. Its main limitation is to solve combinatorial optimization problems, characterized by using variables in the discrete domain. To overcome this limitation, we propose to use a two-step binarization technique, which offers a large number of possible options that we call scheme. For this, we use MAB as an algorithm that learns and recommends a binarization schemes during the execution of the iterations (online). With the experiments carried out, we show that it delivers better results in solving the Set Covering problem than using a fixed binarization scheme.

Idioma originalInglés
Título de la publicación alojadaOptimization and Learning - 6th International Conference, OLA 2023, Proceedings
EditoresBernabé Dorronsoro, Francisco Chicano, Gregoire Danoy, El-Ghazali Talbi
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas248-259
Número de páginas12
ISBN (versión impresa)9783031340192
DOI
EstadoPublicada - 2023
Evento6th International Conference on Optimization and Learning, OLA 2023 - Malaga, Espana
Duración: 3 may. 20235 may. 2023

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1824 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia6th International Conference on Optimization and Learning, OLA 2023
País/TerritorioEspana
CiudadMalaga
Período3/05/235/05/23

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