Evolutionary Many-Objective Algorithms for Combinatorial Optimization Problems: A Comparative Study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications
Link
http://link.springer.com/content/pdf/10.1007/s11831-020-09415-3.pdf
Reference56 articles.
1. Tian Y et al (2018) An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility. IEEE Trans Evol Comput 22(4):609–622
2. He C et al (2017) A radial space division based evolutionary algorithm for many-objective optimization. Appl Soft Comput 61:603–621
3. Li T, Li J (2018) Using modified determinantal point process sampling to update population. In: 2018 IEEE congress on evolutionary computation (CEC). IEEE
4. Deb K (2014) Multi-objective optimization. Search methodologies. Springer, Berlin, pp 403–449
5. Marler RT, Arora JS (2004) Survey of multi-objective optimization methods for engineering. Struct Multidiscipl Optim 26(6):369–395
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