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�������պ����ѧѧ�� 2007, Vol. 33 Issue (04) :486-490    DOI:
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�Ź���1, ������1, �����1, �����2*
1. �������պ����ѧ �����ѧԺ, ���� 100083;
2. �й����ӹ���ϵͳ�о��� ���� 100840
Cloud model based algorithm for global optimization of functions
Zhang Guangwei1, Kang Jianchu1, Li Hesong1, Li Deyi2*
1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. China Electronic System Engineering Company, Beijing 100840, China

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Abstract�� Numerical optimization of given objective functions is a crucial task in many scientific problems. Based on the outstanding characteristics of cloud model on the process of transforming a qualitative concept to a set of quantitative numerical values, and integrate with the basic principle of genetic algorithm, a novel adaptive evolutionary algorithm for continuous global optimization problems was proposed. With the instructions of qualitative knowledge, the extent of searching space is self-adjusted and the possibility of premature and the probability of trapping in local best optimization are greatly reduced, so the algorithm can find high accurate numerical solution within a short time. The algorithm avoids the process of coding and crossover so it is easy to be carried out. By the experiments on typical test functions, the precision, stability and convergence rate were well proved.
Keywords�� genetic algorithm   cloud model   optimization     
Received 2006-04-21;

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About author: �Ź���(1970-),��,ɽ��������, ��ʿ��, ezhang@263.net.
�Ź���, ������, �����, �����.������ģ�͵�ȫ�����Ż��㷨[J]  �������պ����ѧѧ��, 2007,V33(04): 486-490
Zhang Guangwei, Kang Jianchu, Li Hesong, Li Deyi.Cloud model based algorithm for global optimization of functions[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2007,V33(04): 486-490
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