SciELO - Scientific Electronic Library Online

 
vol.20 issue1Design of a Speed Adaptive Controller for a PMSM using Artificial Intelligence(Hyper)sequent Calculi for the ALC(S4) Description Logics author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

KUMAR, Ajit; KUMAR, Dharmender  and  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.

Keywords : Swarm based algorithm; artificial bee colony; optimization; selection scheme.

        · text in English     · English ( pdf )