A multi-objective Artificial Bee Colony for optimizing multi-objective problems

This work proposes a multi-objective artificial bee colony (MOABC) for optimizing problems with multiple objectives. We have adapted the original Artificial Bee Colony (ABC) algorithm to multi objective problems with a grid-based approach for maintaining and adaptively assessing the Pareto front. The Pareto set is used to control the flying behaviours of the individuals and structuring the bee colony. The proposed algorithm was evaluated upon numerical benchmark problems. Our experimental results indicate that the proposed approach is highly competitive compared to other algorithms considered in this work.