A survey: algorithms simulating bee swarm intelligence


KARABOĞA D. , AKAY B.

ARTIFICIAL INTELLIGENCE REVIEW, vol.31, pp.61-85, 2009 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Review
  • Volume: 31
  • Publication Date: 2009
  • Doi Number: 10.1007/s10462-009-9127-4
  • Title of Journal : ARTIFICIAL INTELLIGENCE REVIEW
  • Page Numbers: pp.61-85
  • Keywords: Bee swarm intelligence, Task allocation, Bee foraging, Bee mating, Collective decision, HONEYBEE MATING OPTIMIZATION, ANT COLONY OPTIMIZATION, DIVISION-OF-LABOR, MULTIAGENT SYSTEMS, BEHAVIOR, EFFICIENT, ARCHITECTURE, OPERATOR, BEEHIVE, SOLVE

Abstract

Swarm intelligence is an emerging area in the field of optimization and researchers have developed various algorithms by modeling the behaviors of different swarm of animals and insects such as ants, termites, bees, birds, fishes. In 1990s, Ant Colony Optimization based on ant swarm and Particle Swarm Optimization based on bird flocks and fish schools have been introduced and they have been applied to solve optimization problems in various areas within a time of two decade. However, the intelligent behaviors of bee swarm have inspired the researchers especially during the last decade to develop new algorithms. This work presents a survey of the algorithms described based on the intelligence in bee swarms and their applications.