University of science of Beijing

Beijing, China

University of science of Beijing

Beijing, China
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Yao F.,University of science of Beijing | Yao F.,University of Science and Technology Beijing | Yang W.-D.,University of science of Beijing | Yang W.-D.,University of Science and Technology Beijing | And 2 more authors.
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2010

A multi-objective evolutionary algorithm based on differential evolution is proposed, which takes the selection by the non-dominated sorting and crowding distance. While ensuring the convergence to the Pareto optimal solution set, this algirithm also increases the diversity of individual distribution. In the simulation comparison with non-dominated sorting in genetic algorithms II(NSGA II), the multi-objective differential evolutionary algorithm is better than the NSGA II algorithm both in convergence and in diversity. Finally, this algorithm is applied to the load distribution calculation of hot strip mills with given expressions of objective functions.

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