SciELO - Scientific Electronic Library Online

 
vol.20 número1Diseño de un controlador de velocidad adaptativo para un MSIP utilizando inteligencia artificial(Hyper)sequent Calculi for the ALC(S4) Description Logics índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Computación y Sistemas

versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546

Resumo

KUMAR, Ajit; KUMAR, Dharmender  e  JARIAL, S.K.. A Comparative Analysis of Selection Schemes in the Artificial Bee Colony Algorithm. Comp. y Sist. [online]. 2016, vol.20, n.1, pp.55-66. ISSN 2007-9737.  https://doi.org/10.13053/cys-20-1-2228.

The Artificial Bee Colony (ABC) algorithm is a popular swarm based algorithm inspired by the intelligent foraging behavior of honey bees. In the past, many swarm intelligence based techniques were introduced and proved their effective performance in solving various optimization problems. The exploitation of food sources is performed by onlooker bees in accordance with a proportional selection scheme that can be further modified to avoid such shortcomings as population diversity and premature convergence. In this paper, different selection schemes, namely, tournament selection, truncation selection, disruptive selection, linear dynamic scaling, linear ranking, sigma truncation, and exponential ranking have been used to analyze the performance of the ABC algorithm by testing on standard benchmark functions. From the simulation results, the schemes other than the standard ABC prove their efficient performance.

Palavras-chave : Swarm based algorithm; artificial bee colony; optimization; selection scheme.

        · texto em Inglês     · Inglês ( pdf )