An acceleration-based prediction strategy for dynamic multi-objective optimization
Author:
Funder
Innovative Research Group Project of the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-09157-x.pdf
Reference47 articles.
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2. Aragn VS, Esquivel SC (2004) An evolutionary algorithm to track changes of optimum value locations in dynamic environments. J Comput Sci Technol 4:127–133
3. Bui LT, Michalewicz Z (2010) An evolutionary multi-objective approach for dynamic mission planning. IEEE Cong Evolut Comp. https://doi.org/10.1109/CEC.2010.5586343
4. Chen H, Li M, Chen X (2009) Using diversity as an additional-objective in dynamic multi-objective optimization algorithms. Sec Int Symp Elect Comm Sec 2009:484–487. https://doi.org/10.1109/ISECS.2009.42
5. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197. https://doi.org/10.1109/4235.996017
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