团队进度算法及其应用

Yiming Tang, Yarning Bo, Lei Zhu, Ming Zhang, Yurnei Chang, Ye Ran
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引用次数: 3

摘要

许多被视为优化问题的工程问题都可以用智能优化算法成功地解决,其中一种被称为团队进度算法(TPA)。它是一种新颖的双群体进化算法,模拟了团队成员学习、探索和更新的升级过程,具有全局搜索、局部搜索和定向搜索的能力。TPA的内在机制使其在解决优化问题时具有很强的竞争力。本文主要介绍了TPA的发展和改进,包括TPA的初始过程、几项完善研究及其在微波元件和天线设计中的应用。现有文献的数值结果和设计实例很好地验证了TPA在各类工程优化中的准确性、有效性和可行性。
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Team Progress Algorithm and its Applications
Many popular engineering problems, regarded as optimization problems, can be successfully solved with intelligent optimization algorithms, one of which is named Team Progress Algorithm (TPA). It is a novel kind of two-group evolutionary algorithm that simulates a team upgrading process with member learning, exploring and renewal, possessing the abilities of global, local and directional search. The intrinsic mechanism of TPA makes itself highly competitive in solving optimization problems. This paper mainly focuses on the development and improvement of TPA, including the original procedure, several perfection researches and their applications in microwave component and antenna designs. The numerical results and design examples in available literatures well verify the accuracy, efficiency and feasibility of TPA in the engineering optimizations of all kinds.
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