Title :
On Improved Parallel Immune Quantum Evolutionary Algorithm Based on Learning Mechanism
Author :
Xiaoming You ; Sheng Liu ; Dianxun Shuai
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Univ. of Sci. & Technol., Shanghai
Abstract :
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
Keywords :
evolutionary computation; learning (artificial intelligence); quantum computing; quantum entanglement; learning mechanism; multiuniverse parallel immune quantum evolutionary algorithm; quantum computing; quantum entanglement; quantum interaction; self-adaptive operator; Computer science; Evolution (biology); Evolutionary computation; Immune system; Learning systems; Performance evaluation; Quantum computing; Quantum entanglement; Quantum mechanics; Testing;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.209
