Fitness based Mutation in Artificial Bee Colony Algorithm

Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence based nature inspired algorithm which has been proved a competitive algorithm with some popular nature-inspired algorithms. However, it is found that the ABC algorithm prefers exploration at the cost of the exploitation. Therefore, in this paper a self adaptive fitness based mutation strategy is presented in which the perturbation in the solution is based on fitness of the solution. The proposed strategy is self-adaptive in nature and therefore no manual parameter setting is required.