.png){kind=icon}
返回
A new QPSO based hybrid algorithm for constrained optimization problems via tournamenting process
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-019-04601-3.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The goal of this paper is to propose a new hybrid algorithm based on advanced quantum behaved particle swarm optimization (QPSO) technique and binary tournamenting for solving constrained optimization problems. In binary tournamenting, six different situations/options are considered and accordingly six variants of hybrid algorithms are proposed. Then to test the efficiency and performance of these algorithms and also to select the best algorithm among these, six benchmark optimization problems are selected and solved. Then the computational results are compared graphically as well as numerically. Finally, the best found algorithm is applied to solve three engineering design problems and the computational results are compared with the existing algorithms available in the literature.
Keyword:
Constrained optimization
PSO
Adaptive QPSO
Gaussian QPSO
Tournamenting
Hybrid algorithm
Engineering design problem
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
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
.png){kind=icon}
A study of interval metric and its application in multi-objective optimization with interval objectives区间度量及其在区间目标多目标优化中的应用研究
PREAI
分享收藏Facile synthesis of α-MnO2 nanorods at low temperature and their microwave absorption properties
PREAI
分享收藏
查看更多内容