Harmony-based monarch butterfly optimization algorithm
Mohamed Ghetas, Chan Huah Yong, Putra Sumari · 2015
Monarch butterfly optimization (MBO) is a new metaheuristic algorithm mimics the migration of butterflies from northern USA to Mexico. In MBO, there are mainly two processes. In the first process, the algorithm emulates how some of the butterflies move from the current position to the new position by the migration operator. In the latter process, the algorithm tunes the position of other butterflies by adjusting operator. In order to enhance the search ability of MBO, an innovation method called MBHS is introduced to tackle the optimization problem. In MBHS, the harmony search (HS) adds mutation operators to the process of adjusting operator to enhance the exploitation, exploration ability, and speed up the convergence rate of MBO. For the purpose to validate the performance of MBHS, 14 benchmark functions are used, and the performance is compared with well-known search algorithms. The experimental results demonstrate that MBHS performs better than the basic MBO and other algorithms.