增强布谷鸟智能搜索算法

I. I. Aina, O. J. Peter, A. Ayoade, F. Oguntolu, M. Oluwayemi
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引用次数: 0

摘要

布谷鸟搜索(CS)算法是一种元启发式算法,具有许多优点。例如,该方法易于应用,可调参数少,适用于求解优化问题。但由于布谷鸟搜索参数保持不变,容易陷入局部最优,且收敛速度慢。为了解决这一问题,本文提出了一种改进的CS算法——增强布谷鸟智能搜索(ECIS)算法。通过一些基准约束优化测试函数对ECIS的效率进行了测试,结果表明ECIS比CS给出了更好的最优值。
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Enhanced Cuckoo Intelligence Search Algorithm
Cuckoo Search (CS) algorithm is a meta-heuristic technique that displays several merits. For example, it is easier to apply and less tuning parameters also, it is suitable for solving optimization problems. However, easily fall into local optimum has been established and has a slow convergence rate as a result of the cuckoo search parameters being kept constant. Therefore to handle this issue, an Enhanced Cuckoo Intelligence Search (ECIS) algorithm was developed which is an upgraded CS algorithm. The efficiency of ECIS was tested by some benchmark constrained optimization test functions and it was shown that ECIS gives a better optimal value than CS.
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来源期刊
International Journal of Difference Equations
International Journal of Difference Equations Engineering-Computational Mechanics
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