计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 231-233.

• 人工智能 • 上一篇    下一篇

爆炸搜索算法及其收敛性证明

曹炬,侯学卿   

  1. (华中科技大学大学数学与统计学院 武汉430074)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Explosion Search Algorithm and its Convergence

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

摘要: 受烟花(炸弹)爆炸的启发,结合经典优化算法提出了一种新的智能优化算法—爆炸搜索算法(Explosion Search Algorithm, ESA) 。ESA引入部域搜索的思想,将智能优化算法与下降搜索算法进行有机结合,使得ESA具有强大的局部搜索能力和全局搜索能力以及好的收敛精度。对算法的收敛性进行了证明,最后通过对benchmark函数集进行仿真并同其他算法进行比较,验证了ESA的高效性。

关键词: 智能优化算法,爆炸搜索算法,差商最速下降搜索,邻域搜索,收敛

Abstract: Inspired by explosion of fireworks(bomb) , a new intelligence search algorithm was proposed, which is called Explosion Search Algorithm(ESA). One theory defined as Neighborhood Search was proposed in ESA, the Steepest descent search algorithm was introduced into the ESA,which makes this new algorithm stronger ability of global search as well as local search. The convergence of the algorithm was also proved in this article. The simulation using standard benchmark functions and comparison with other algorithms proved the efficiency of the new algorithm.

Key words: Intelligence optimization algorithm, Explosion search algorithm, Difference steepest descent search, Neigh-borhood search,Convergence

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