From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms

被引：1
|
作者：
Yang, Xin-She [1 ]
Deb, Suash [2 ,3 ]
Fong, Simon [4 ]
He, Xingshi [5 ]
Zhao, Yu-Xin [6 ]
机构：
[1] Middlesex Univ, Modeling & Optimizat, London N17 8HR, England
[2] Stanford Univ, Comp Sci, Stanford, CA 94305 USA
[3] Int Neural Network Soc, Stanford, CA USA
[4] Univ Macau, Dept Comp & Informat Sci, Taipa, Peoples R China
[5] Xian Polytech Univ, Coll Sci, Xian, Peoples R China
[6] Harbin Engn Univ, Control & Nav, Harbin, Peoples R China
来源：
COMPUTER | 2016年 / 49卷 / 09期
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Nature has provided rich models for computational problem solving, including optimizations based on the swarm intelligence exhibited by fireflies, bats, and ants. These models can stimulate computer scientists to think nontraditionally in creating tools to address application design challenges.
引用
收藏
页码：52 / 59
页数：8
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