The application of genetic operators in the Artificial Bee Colony algorithm

Stochastic population based algorithms have become a popular way to solve large optimization problems. Several Evolutionary or Swarm based search algorithms, such as Genetic Algorithms and Artificial Bee Colony (ABC) have been in use for quite some time. The ABC has found application in protein folding, face recognition and neural network training. The ABC, however, shows variance in its runs. This paper proposes a modification to the ABC which reduced this variation. After briefly covering and comparing both the algorithms, the paper proposes modification to Artificial Bee Colony Algorithm which aims at controlling variation. It concludes by analyzing the modification and outlining future work.