Enhancing the food locations in an Artificial Bee Colony algorithm

Artificial Bee Colony or ABC is one of the newest additions to the class of population based Nature Inspired Algorithms (NIA). In the present study we suggest some modifications in the structure of basic ABC to further improve its performance. The corresponding algorithm proposed in the present study is named Intermediate ABC (I-ABC). In I-ABC, the potential food sources are generated by using the intermediate positions between the uniformly generated random numbers and random numbers generated by opposition based learning (OBL). The proposed I-ABC is further modified by guiding the bees towards the best food location. I-ABC is validated on a set of 15 benchmark problems with bound constraints. The numerical results indicate the competence of the proposed I-ABC algorithm.