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- W2350290420 abstract "In this paper,a hybrid mutation clonal selection multiobjective optimization algorithm was presented.In the algorithm,evolution was performed in three antibody groups,every group used different mutation operator,through the updated external memory antibody population to keep the Pareto optimal solution.The large-scale mutation operator could be utilized to quickly localize the global Pareto optimal space,the small-scale mutation operator could implement local accurate Pareto optimal solution search,and the uniform mutation operator could make the algorithm have the ability to escape from local optimal solution,which ensured the diversity of the algorithm.We compared the proposed method with NSGA-II,e-MOEA and the multiobjective clonal selection algorithm(MCSA) based on the signal group in solving five DTLZ problems,and the experimental results show that the new algorithm is effective." @default.
- W2350290420 created "2016-06-24" @default.
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- W2350290420 date "2011-01-01" @default.
- W2350290420 modified "2023-09-24" @default.
- W2350290420 title "Hybrid Mutation Clonal Selection Multiobjective Optimization Algorithm" @default.
- W2350290420 hasPublicationYear "2011" @default.
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