Author:
Zhao Haitong,Zhang Changsheng,Ning Jiaxu,Zhang Bin,Sun Peng,Feng Yunfei
Funder
National Natural Science Foundation Program of China
Special Fund for Fundamental Research of Central Universities of Northeastern University
Publisher
Springer Science and Business Media LLC
Reference90 articles.
1. Ishibuchi, H., Setoguchi, Y., Masuda, H., et al.: Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes. IEEE Trans. Evol. Comput. 21(2), 169–190 (2017)
2. Srinivas, S.N., Deb, K.: Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evolut. Comput. 2(3), 221–248 (1994)
3. Horn, J., Nafpliotis, N., Goldberg, D.E.: A niched Pareto genetic algorithm for multiobjective optimization. In: IEEE World Congress on Computational Intelligence, Proceedings of the First IEEE Conference on Evolutionary Computation, 1994. IEEE Xplore, vol. 1, pp. 82–87
4. Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257–271 (1999)
5. Deb, K., Pratap, A., Agarwal, S., et al.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
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