.png){kind=icon}
返回
Improved fireworks algorithm with information exchange for function optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.knosys.2018.08.016.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The fireworks algorithm, which is inspired by the explosion of fireworks, is a new swarm-based meta heuristic algorithm for global optimization. This work proposes an improved fireworks optimization algorithm (IFWA) based on the enhanced fireworks algorithm (EFWA). Three aspects of improvement are presented after an analysis of the drawbacks of EFWA. These improvements are a new explosion scheme, GS-Gaussian explosion operator, and deep information exchange strategy. The proposed IFWA is tested on 23 benchmark function optimization problems and a real engineering problem, namely, optimal controller design for automotive active suspension. Optimization results prove that IFWA has competitive advantage compared with EFWA and other popular meta-heuristic algorithms and demonstrates the potential to solve real problems effectively. (C) 2018 Elsevier B.V. All rights reserved.
Keyword:
Fireworks algorithm
Swarm intelligence
Function optimization
LQR controller
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
Survey of advanced suspension developments and related optimal control applications.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏分享收藏
查看更多内容