An idea based on Honey Bee Swarm for Numerical Optimization

Abstract

Swarm intelligence has become a re search interest to many research scientists of related fields in recent years. Bonabeau has defined the swarm intelligence as “any attempt to design algorithms or distributed problem-solving devi ces inspired by the co llective behaviour of social insect colonies and other animal societies” [1]. Bonabeau et al. focused their viewpoint on social insects alone such as termites, bees , wasps as well as other different ant species. However, the term swarm is used in a general manner to refer to any restrained collection of interacting agents or individua ls. The classical example of a swarm is bees swarming around their hive; nevertheless the metaphor can easily be extended to other systems with a similar architecture. An ant colony can be thought of as a swarm whose individual agents are ants. Similarly a flock of birds is a swarm of birds. An immune system [2] is a swarm of cells and molecules as well as a crowd is a swarm of people [3]. Particle Swarm Optimization (PSO) Algorithm models the social behaviour of bird flocking or fish schooling [4]