.png){kind=icon}
返回
Integrating mutation operator into grasshopper optimization algorithm for global optimization
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-021-05752-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The major purpose of this article is to enhance the performance of GOA algorithm by integrating a new mutation operator to the standard GOA algorithm. A series of six different variants of enhanced GOA is proposed by integrating GOA with six different variants of the mutation operator. The new enhanced metaheuristic optimization method is called EGOAs. EGOA aims to address the problems of slow convergence and trapping into local optima, by achieving a good balance between exploration and exploitation, using a special mutation operator that enhances the diversity of the standard GOA, to find the best solution for global optimization problems. The implementation process for enhancing the GOA algorithm is presented and the effectiveness of the enhanced algorithm is evaluated against 60 of the optimization benchmark functions, and compared to that of the standard GOA, as well as to other metaheuristic optimization algorithms. The performance of EGOAs was compared with the other improved methods based on GOA. Experimental results show that EGOAs is clearly superior to the standard GOA algorithm, as well as to other well-known algorithms, in terms of achieving the best optimal value, convergence speed, and avoiding local minima, which makes EGOAs a promising addition to the arsenal of metaheuristic algorithms.
Keyword:
Global optimization problem
Grasshopper optimization algorithm
Mutation operator
Test functions
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Kinematic and kinetic differences in the execution of vertical jumps between people with good and poor ankle joint dorsiflexion踝关节背屈良好和不良的人在执行垂直跳跃时的运动学和动力学差异
PREAI
分享收藏Closed determination of the number of neurons in the hidden layer of a multi-layered perceptron network.png)
SOFT COMPUTING
SOFT COMPUTINGIF2.5
PREAI
分享收藏Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm蛾焰优化算法: 一种新的自然启发启发式范式
PREAI
分享收藏Moth-flame swarm optimization with neutrosophic sets for automatic mitosis detection in breast cancer histology imagesAPPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
分享收藏
分享收藏分享收藏PREVALENCE OF CHILDHOOD OBESITY AND ITS SOCIO-PSYCHOLOGICAL EFFECTS ON PRIMARY SCHOOL CHILDREN IN THE CAPE COAST METROPOLIS, GHANA加纳 Cape Coast 首都地区小学生儿童肥胖的患病率及其社会心理影响
OAAI
OAAI分享收藏
查看更多内容