Artificial Bee colony and its Application: An Overview

The Artificial Bee Colony is a swarm based meta-heuristic algorithm for optimizing numerical based problem and provides the solution with accuracy and less effort, cost, time and space. Here the word meta heuristic means to provide a better solution to the given problem especially in the case of incomplete or imperfect information. In ABC algorithm, bees search best food source from many food sources and during searching best source, it consider various parameter like nectar amount (fitness value of food source), time etc. This algorithm was inspired by the foraging behavior of honey bees swarm, to look for the best solution to an optimization problem. The model which uses this algorithm has 3 essential components: Employed bees, Unemployed bees and the food sources. The employed or scout bees basically wander for the rich food sources which can be close to their hive. In this algorithm, a crowd of artificial forager bees that are the agents of the environment starts searches for the rich food sources i.e. the good solution for the given problem. and to apply this algorithm, the examined optimization problem is first transformed to the problem of analyzing the best parameter vectors for the given array vectors to minimizes the objective function. Then the artificial bees randomly and unexpectedly find a population of initial solution vectors which can be then improved by employing some strategies i.e. forwarding towards the better solutions in terms of neighbour search parameter mechanism.