Constrained solution of CEC 2017 with monarch butterfly optimisation

Abstract

Recently, inspired by the behaviour of monarch butterfly in North America, Wang et al. proposed a new kind of swarm intelligence algorithm, called Monarch Butterfly Optimisation (MBO). Since it was proposed, it has been widely studied and applied in various engineering fields. In this paper, we apply MBO algorithm to solve CEC 2017 competition on constrained real-parameter optimisation. Also, the performance of MBO on 21 constrained CEC 2017 real-parameter optimisation problems is compared with five other state-of-the-art evolutionary algorithms. The experimental results indicate that MBO algorithm performs much better than other five evolutionary algorithms on most cases. It is strongly proven that MBO is a very promising algorithm for solving constrained engineering problems.