全局最优位置在粒子群优化算法中的应用

2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) Pub Date : 2018-07-01 DOI:10.1109/ICEAST.2018.8434504

Varothon Cheypoca, K. Siriboon, B. Kruatrachue

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引用次数: 6

摘要

研究了粒子群算法陷入局部最优时，粒子最优位置(GBEST)在重新运行中的应用。重新初始化粒子位置通常用于重新启动粒子群算法，以便在陷入局部最优时获得更好的结果。本文提出利用GBEST进一步迫使粒子运动出先前的局部最优，而不是仅仅重置GBEST。该方法在26个基准测试函数上进行了测试，结果令人满意。

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The Use of Global Best Position in Rerun of Particle Swarm Optimization

This paper studies the use of particle best position (GBEST) in rerun when particle swarm optimization (PSO) traps in local optima. Reinitialize particles positions are often used to restart PSO to get better results when trapping in local optima. This paper proposed the use of GBEST to further force particle movement out of previous local optima instead of only reset GBEST. The proposed method is tested on 26 benchmark test functions with satisfactory results.

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来源期刊

2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST)

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