Abstract
The NSGA-II algorithm is widely used in multi-objective optimization problems, but the traditional NSGA-II algorithm has some shortcomings such as large computational cost and poor convergence in some complex practical problems. To solve above defections, an improved NSGA-II algorithm is proposed in this paper. Firstly, the specific crossover and mutation operators are designed. Secondly, a novel elitist strategy is developed as well. Then, the simulations of the standard test functions are carried out, the results illustrate that the improved strategies can effectively enhance the convergence and operation speed of the traditional algorithm. Finally, in order to test the practicality of the algorithm, a multi-objective mathematical model for charge plan of steelmaking is established. Simulation is carried out with real industry data. The results show that the algorithm is practical for charge scheduling.
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Zhang, X., Liu, Z., Wang, C., Shang, Y. (2019). An Improved NSGA-II Algorithm and Its Application. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1137. Springer, Singapore. https://doi.org/10.1007/978-981-15-1922-2_41
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DOI: https://doi.org/10.1007/978-981-15-1922-2_41
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