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�������պ����ѧѧ�� 2011, Vol. 37 Issue (9) :1132-1136    DOI:
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Adaptive parallel simulated annealing genetic algorithms based on cloud models
Dong Lili, Gong Guanghong, Li Ni, Sun Yong*
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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Abstract�� Due to the shortcomings of genetic algorithms such as the low convergence rate and premature convergence, an improved genetic algorithms was proposed, called adaptive parallel simulated annealing genetic algorithms based on cloud models (PCASAGA). PCASAGA applied cloud models to the adaptive regulation of the crossover probability and mutation probability. Simulated annealing was combined to prevent genetic algorithms from local optimum. Multi-species optimization mechanism was used to realize algorithm parallel operation. Intel-s threading building blocks (TBB) parallel technology was also used to realize algorithm parallel execution on multi-core computers. Theoretical analysis and simulation results verify that PCASAGA has better convergence speed and optimal results than original or improved genetic algorithms, and it takes full advantage of the current computers multi-core resources.
Keywords�� genetic algorithms   simulated annealing   cloud model   adaptive mechanism   parallel     
Received 2010-04-20;
Fund:

������Ȼ��ѧ����������Ŀ(61004089);��������ʿ�����������Ŀ(20091102120013)

About author: ������(1986-),Ů,��������,˶ʿ��,donglili1986@163.com.
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������, �����, ����, ����.������ģ�͵�����Ӧ����ģ���˻��Ŵ��㷨[J]  �������պ����ѧѧ��, 2011,V37(9): 1132-1136
Dong Lili, Gong Guanghong, Li Ni, Sun Yong.Adaptive parallel simulated annealing genetic algorithms based on cloud models[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2011,V37(9): 1132-1136
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