基于资源竞争算法的磁致动器优化

Q2 Social Sciences

Advances in Engineering Education Pub Date : 2017-11-01 DOI:10.1109/PIERS-FALL.2017.8293204

H. Bouchekara, M. Nahas

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引用次数: 1

摘要

在过去的几年里，全局优化领域非常活跃，产生了各种各样的优化算法，特别是在元启发式领域。目前，元启发式算法以其简单和具有竞争力的性能被广泛应用于各个领域的优化问题求解。资源竞争(COR)是一种基于动物群体竞争行为的自然现象启发的新型元启发式算法。本文提出了COR算法，并将其应用于某磁致动器基准的优化。研究结果表明，COR算法具有很强的竞争力，为磁致动器的优化设计提供了一种可靠的替代方法。

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Optimization of magnetic actuators using competition over resources algorithm

Over the last few years, the field of global optimization has been very active producing a wide range of optimization algorithms, particularly in the field of metaheuristics. Nowadays, metaheuristics are extensively used to solve optimization problems in all fields due to their simplicity and competitive performance. Competition Over Resource (COR) is a novel metaheuristic algorithm inspired by a natural phenomenon that is based on the competitive behavior of animal groups. In this paper, the COR algorithm is presented and then applied to optimize a magnetic actuator benchmark. The results obtained in the paper indicate that the COR algorithm is very competitive and therefore offers a reliable alternative method for the optimal design of magnetic actuators.

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来源期刊

Advances in Engineering Education Social Sciences-Education

CiteScore

2.90

自引率

0.00%

发文量

期刊介绍： The journal publishes articles on a wide variety of topics related to documented advances in engineering education practice. Topics may include but are not limited to innovations in course and curriculum design, teaching, and assessment both within and outside of the classroom that have led to improved student learning.