计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 237-244.doi: 10.11896/j.issn.1002-137X.2017.10.043

• 人工智能 • 上一篇    下一篇

生态金字塔粒子群优化算法

刘亚红,张玮,樊吕彬   

  1. 太原理工大学化学化工学院 太原030024,太原理工大学化学化工学院 太原030024,太原理工大学化学化工学院 太原030024
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受山西省自然科学基金资助

Ecological Pyramid Particle Swarm Optimization

LIU Ya-hong, ZHANG Wei and FAN Lv-bin   

  • Online:2018-12-01 Published:2018-12-01

摘要: 为解决粒子群优化算法在处理高维复杂函数时容易陷入局部最优和早熟收敛的问题,提出生态金字塔粒子群优化算法(EP-PSO)。该算法引入生态金字塔系统,使粒子在搜索空间分等级、分子群寻优,有效增加了群体多样性;为增强算法的全局搜索能力,对处于停滞状态的个体极值和全局极值进行动态变异,以达到扩大种群潜在搜索空间的效果。选择15个测试函数验证算法的有效性,结果表明EP-PSO有着良好的寻优性能,能够得到较高精度解,具有较高的效率和可信度。

关键词: 粒子群优化算法,早熟收敛,生态金字塔系统

Abstract: A novel ecological pyramid particle swarm optimization variant was proposed to deal with the high dimensions,complex optimization problems.In the new variant,the ecological pyramid system was introduced to improve the particle’s diversity.At the same time,the variation both on the local exemplar and the global exemplar was also employed extending the search space.To verify the effectiveness of the algorithm,fifteen benchmark problems were used to test the performance of EP-PSO.Experimental results validate the outstanding performance of EP-PSO.Compared with other algorithms,EP-PSO not only obtained high accuracy solutions,but also achieved high efficiency and reliability.

Key words: Particle swarm optimization algorithm,Premature convergence,Ecological pyramid system

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