Multiobjective Krill Herd Algorithm for Electromagnetic Optimization

Metaheuristics have recently become the forefront of the current research as a powerful way to deal with many electromagnetic optimization problems. Based on the simulation of the herding behavior of krill individuals, a krill herd (KH) algorithm was recently proposed to solve optimization problems. In order to extend the classical mono-objective KH algorithm approach, this paper proposes a new multiobjective KH (MOKH) algorithm and a modified MOKH approach using the beta distribution in the inertia weight tuning. Numerical results on a multiobjective constrained brushless direct current motor design problem show that the evaluated MOKH algorithms present a promising performance.