An Improved Artificial Bee Colony Algorithm for Optimal Design of Electromagnetic Devices

Optimal design problems of electromagnetic devices are generally multimodal, nondifferentiable, and constrained. This makes metaheuristic algorithm a good choice for solving such problems. In this paper, a newly developed metaheuristic algorithm is presented to address the aforementioned issues. The proposed algorithm is based on the paradigm of artificial bee colony (ABC). A drawback of the original ABC algorithm is because its solution variation is only 1-D, as this decreases its convergence speed. In this paper, a one-position inheritance scheme is proposed to alleviate this drawback. An opposite directional (OD) search is also proposed to accelerate the convergence of the ABC algorithm. The novel algorithm is applied to both TEAM Workshop problem 22 and a loudspeaker design problem. Both discrete and continuous cases of problem 22 are tested. The effectiveness and efficiency of the proposed algorithm are demonstrated by comparing its performance with those of the original ABC, an improved ABC known as Gaussian ABC, and differential evolution algorithms.