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摘要

本文研究并提出了一套新的针对电磁问题的蚁群优化算法(ACOR)。自适应ACOR在迭代过程中调整其参数,以控制全局最优搜索中勘探开发的参与和执行。该策略是在探索和利用之间平稳交替,前者在算法的初始阶段占主导地位,后者在算法的最后阶段占主导地位。虽然所提出的算法可以应用于任何类型的优化问题,但它们经过了调整,并且在电磁基准问题(即Loney螺线管)上证明了它们的效率。
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Adaptive ACOR to solve the Loney’s solenoid electromagnetic problem
This paper studies and proposes a new set of ACOR (Ant Colony optimization for Real domains) algorithms dedicated to electromagnetic problems. The adaptive ACOR adjust their parameters during the iterative process in order to control how the exploration and exploitation are involved and performed in the global optimum search. The strategy is to smoothly alternate between exploration and exploitation, with the first one predominant in the initial stages of the algorithms and the second towards the end. Though the proposed algorithms can be applied to any kind of optimization problem they are tuned and their efficiency is proven on an electromagnetic benchmark problem, namely Loney’s solenoid.
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