.png){kind=icon}
返回
Comparison among five evolutionary-based optimization algorithms
.png){kind=icon}
PRE
AI
DOI：10.1016/j.aei.2005.01.004.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical techniques may fail. This paper compares the formulation and results of five recent evolutionary-based algorithms: genetic algorithms, memetic algorithms, particle swarm, ant-colony systems, and shuffled frog leaping. A brief description of each algorithm is presented along with a pseudocode to facilitate the implementation and use of such algorithms by researchers and practitioners. Benchmark comparisons among the algorithms are presented for both continuous and discrete optimization problems, in terms of processing time, convergence speed, and quality of the results. Based on this comparative analysis, the performance of EAs is discussed along with some guidelines for determining the best operators for each algorithm. The study presents sophisticated ideas in a simplified form that should be beneficial to both practitioners and researchers involved in solving optimization problems. (C) 2005 Elsevier Ltd. All rights reserved.
Keyword:
evolutionary algorithms
genetic algorithms
memetic algorithms
particle swarm
ant colony
shuffled frog leaping
optimization
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:
9.9
论文数:
4.1K
被引数:
1.7W
机构
暂无机构信息
引用论文
Modeling of the Chemical Looping Combustion of Hard Coal and Biomass Using Ilmenite as the Oxygen Carrier.png)
Energies
OAAI
EnergiesIF0
OAAI分享收藏
Optimization of water distribution network design using the Shuffled Frog Leaping Algorithm基于混合蛙跳算法的供水管网优化设计
PREAI
分享收藏分享收藏
查看更多内容