On improved Parallel Immune Quantum Evolutionary Algorithm based on Learning Mechanism

被引：0
|
作者：
You, Xiaoming [1 ,2 ]
Liu, Sheng [1 ,2 ]
Shuai, Dianxun [1 ]
You, Xiaoming [1 ,2 ]
Liu, Sheng [1 ,2 ]
机构：
[1] East China Univ Sci & Technol, Dept Comp Sci & Technol, Shanghai, Peoples R China
[2] Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai, Peoples R China
来源：
ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1 | 2006年
关键词：
Parallel Quantum Evolution Algorithm; Immune Quantum Evolution Algorithm; self-adaptive operator; quantum computing;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new Multi-universe Parallel Immune Quantum Evolutionary Algorithm based on Learning Mechanism (MPMQEA) is proposed, in the algorithm, all individuals are divided into some independent sub-colonies, called universes. Their topological structure is defined, each universe evolving independently uses the immune quantum evolutionary algorithm; Information among the universes is exchanged by adopting emigration based on the improved learning mechanism and quantum interaction simulating entanglement of quantum. It not only can maintain quite nicely the population diversity, but also can help to converge to the global optimal solution rapidly. The typical function tests show that MPMQEA has nice performances such as avoiding local optima, high precision solution, and quick convergence.
引用
收藏
页码：908 / 913
页数：6
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