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An adaptive immune optimization algorithm for energy minimization problems
Authors:Shao Xueguang  Cheng Longjiu  Cai Wensheng
Affiliation:Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, 230026, People's Republic of China. xshao@ustc.edu.cn
Abstract:Based on the immune theory of biology, a novel evolutionary algorithm, adaptive immune optimization algorithm (AIOA), is proposed. In AIOA, density regulation and immune selection is adopted to control the individual diversity and the convergence adaptively. By an application of the algorithm to the optimization of test functions, it is shown that the algorithm is a highly efficient optimization method compared with other stochastic optimization methods. The algorithm was also applied to the optimization of Lennard-Jones clusters, and the results show that the method can find the optimal structure of N
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