跳到主要导航 跳到搜索 跳到主要内容

平衡探索与利用的广义鸽群优化算法

  • Shi Cheng
  • , Ming Ming Zhang
  • , Yu Hui Shi*
  • , Hui Lu
  • , Xiu Juan Lei
  • , Rui Wang
  • *此作品的通讯作者
  • Shaanxi Normal University
  • Southern University of Science and Technology
  • National University of Defense Technology

科研成果: 期刊稿件文章同行评审

摘要

A generalized pigeon-inspired optimization (GPIO) algorithm for balancing the exploration and exploitation abilities is proposed herein. The traditional pigeon-inspired optimization algorithm includes two operators, namely the map and compass operator and the landmark operator. These two operators are implemented only for one round at a single run. In the GPIO algorithm, the search process is divided into multiple stages, and two operators are implemented in each stage. These two operators are implemented for multiple rounds at one single run. The map and compass operator focuses on the exploration ability, while the landmark operator focuses on the exploitation ability. The GPIO algorithm changes the execution order of the two operators without additional objective function evaluation. Moreover, the structure of the solutions and the parameter settings are extended in the GPIO algorithm, which is beneficial to search quality improvement. The simulation results show that the GPIO algorithm improves the search efficiency and the search results of the algorithm.

投稿的翻译标题Generalized pigeon-inspired optimization algorithm for balancing exploration and exploitation
源语言繁体中文
页(从-至)268-279
页数12
期刊Scientia Sinica Technologica
53
2
DOI
出版状态已出版 - 2023

关键词

  • exploration and exploitation
  • multimodal optimization
  • pigeon-inspired algorithm
  • swarm intelligence

指纹

探究 '平衡探索与利用的广义鸽群优化算法' 的科研主题。它们共同构成独一无二的指纹。

引用此