.png){kind=icon}
返回
Memory based Hybrid Dragonfly Algorithm for numerical optimization problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2017.04.033.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Dragonfly algorithm (DA) is a recently proposed optimization algorithm based on the static and dynamic swarming behaviour of dragonflies. Due to its simplicity and efficiency, DA has received interest of researchers from different fields. However, it lacks internal memory which may lead to its premature convergence to local optima. To overcome this drawback, we propose a novel Memory based Hybrid Dragonfly Algorithm (MHDA) for solving numerical optimization problems. The pbest and gbest concept of Particle Swarm optimization (PSO) is added to conventional DA to guide the search process for potential candidate solutions and PSO is then initialized with pbest of DA to further exploit the search space. The proposed method combines the exploration capability of DA and exploitation capability of PSO to achieve global optimal solutions. The efficiency of the MHDA is validated by testing on basic unconstrained benchmark functions and CEC 2014 test functions. A comparative performance analysis between MHDA and other powerful optimization algorithms have been carried out and significance of the results is proved by statistical methods. The results show that MHDA gives better performance than conventional DA and PSO. Moreover, it gives competitive results in terms of convergence, accuracy and search-ability when compared with the state-of-the-art algorithms. The efficacy of MHDA in solving real world problems is also explained with three engineering design problems. (C) 2017 Elsevier Ltd. All rights reserved.
Keyword:
Dragonfly algorithm
Particle Swarm Optimization
Hybridization
Benchmark functions
Engineering problems
Friedman's test
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:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
分享收藏Imperialistic Competitive Algorithm: A metaheuristic algorithm for locating the critical slip surface in 2-Dimensional soil slopes帝国竞争算法: 一种用于在二维土坡中定位临界滑动面的元启发式算法.png)
GEOSCIENCE FRONTIERS
OAAI
GEOSCIENCE FRONTIERSIF8.9
OAAI分享收藏Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization求解全局数值优化问题的策略自适应差分进化算法
OAAI
OAAI分享收藏
查看更多内容