A Percentile Transition Ranking Algorithm Applied to Knapsack Problem

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

21 Citas (Scopus)

Resumen

The binarization of Swarm Intelligence continuous metaheuristics is an area of great interest in operational research. This interest is mainly due to the application of binarized metaheuristics to combinatorial problems. In this article we propose a general binarization algorithm called Percentile Transition Ranking Algorithm (PTRA). PTRA uses the percentile concept as a binarization mechanism. In particular we will apply this mechanism to the Cuckoo Search metaheuristic to solve the set multidimensional Knapsack problem (MKP). We provide necessary experiments to investigate the role of key ingredients of the algorithm. Finally to demonstrate the efficiency of our proposal, we solve Knapsack benchmark instances of the literature. These instances show PTRA competes with the state-of-the-art algorithms.

Idioma originalInglés
Título de la publicación alojadaApplied Computational Intelligence and Mathematical Methods - Computational Methods in Systems and Software 2017
EditoresRadek Silhavy, Petr Silhavy, Zdenka Prokopova
EditorialSpringer Verlag
Páginas126-138
Número de páginas13
ISBN (versión impresa)9783319676203
DOI
EstadoPublicada - 2018
Publicado de forma externa
EventoInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017 - Vsetin, República Checa
Duración: 12 sept. 201714 sept. 2017

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen662
ISSN (versión impresa)2194-5357

Conferencia

ConferenciaInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017
País/TerritorioRepública Checa
CiudadVsetin
Período12/09/1714/09/17

Huella

Profundice en los temas de investigación de 'A Percentile Transition Ranking Algorithm Applied to Knapsack Problem'. En conjunto forman una huella única.

Citar esto