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

机译:电磁设备优化设计的改进人工蜂群算法

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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.
机译:电磁设备的最佳设计问题通常是多峰的,不可微的且受约束的。这使得元启发式算法成为解决此类问题的不错选择。在本文中,提出了一种新开发的元启发式算法来解决上述问题。所提出的算法基于人工蜂群(ABC)的范例。原始ABC算法的一个缺点是因为其解决方案变化仅为1-D,因为这会降低其收敛速度。在本文中,提出了一种单位置继承方案以减轻该缺点。还提出了反向搜索(OD),以加快ABC算法的收敛速度。该新颖算法被应用于TEAM Workshop问题22和扬声器设计问题。测试了问题22的离散情况和连续情况。通过将其性能与原始ABC,改进的称为高斯ABC的ABC和差分进化算法的性能进行比较,证明了该算法的有效性和效率。

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