Synergizing fitness learning with proximity-based food source selection in artificial bee colony algorithm for numerical optimization
An improved variant of the ABC algorithm is presented by simulating a learning mechanism. The onlooker bees position is modified using proximity based perturbation scheme and a probabilistic weighted selection strategy. The algorithm is competitive against several state-of-the-art methods for box-constrained continuous optimization. The algorithm also shows competitive performance on a few real world optimization problems.
fitness learning artificial bee colony algorithm swarm intelligence biologically-inspired optimization exploration exploitation