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Alternative TitleResearch on Some Novel Bionic Optimization Algorithms
段海滨; 王道波; 于秀芬; 北京8701信箱
Source Publication计算机仿真
Keyword蚁群算法 微粒群算法 人工免疫算法 人工鱼群算法 比较
Other AbstractBionic optimization algorithms are stochastic search methods that mimic the natural biological behavior of species.They are mainly applied to solve various optimization problems.This paper proposes the formulation of four recent biology-based algorithms;ant colony algorithm,particle swarm optimization algorithm,artificial immune algorithm,and artificial fish-swarm algorithm.A brief description of each algorithm is presented firstly.Then,a de-tailed comparison and analysis of these bionic optimization algorithms are conducted.These bionic optimization algo-rithms are a kind of uncertain algorithm with great probability,and independent from the mathematical characters of different problems.These algorithms also have parallelism and robustness.The different points are embedded in the algorithms.Finally,some remarks on the further research contents and directions are discussed.
Indexed ByCSCD
Funding Project中国科学院空间科学与应用研究中心
Citation statistics
Cited Times:10[CSCD]   [CSCD Record]
Document Type期刊论文
Corresponding Author北京8701信箱
Recommended Citation
GB/T 7714
段海滨,王道波,于秀芬,等. 几种新型仿生优化算法的比较研究[J]. 计算机仿真,2007,24(3):169-172,253.
APA 段海滨,王道波,于秀芬,&北京8701信箱.(2007).几种新型仿生优化算法的比较研究.计算机仿真,24(3),169-172,253.
MLA 段海滨,et al."几种新型仿生优化算法的比较研究".计算机仿真 24.3(2007):169-172,253.
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