Open Access
Issue |
ITM Web Conf.
Volume 59, 2024
II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
|
|
---|---|---|
Article Number | 02022 | |
Number of page(s) | 9 | |
Section | Interdisciplinary Mathematical Modeling and Applications | |
DOI | https://doi.org/10.1051/itmconf/20245902022 | |
Published online | 25 January 2024 |
- F. Vaz, Y. Lavinas, C. Aranha, M. Ladeira, Exploring constraint handling techniques in real-world problems on MOEA/D with limited budget of evaluations, in Proceedings of Evolutionary Multi-Criterion Optimization: 11th International Conference, EMO, March 28–31 2021, Shenzhen, China (2021) [Google Scholar]
- S.C. Brailsford, C.N. Potts, B.M. Smith, European journal of operational research 119(3), 557–581 (1999) [CrossRef] [Google Scholar]
- M.A. Potter, K.A.D. Jong, Evolutionary computation 8, 1–29 (2000) [CrossRef] [Google Scholar]
- A. Neumaier, Acta numerica 13, 271–369 (2004) [CrossRef] [MathSciNet] [Google Scholar]
- A.E. Eiben, Evolutionary algorithms and constraint satisfaction: Definitions, survey, methodology, and research directions, Theoretical aspects of evolutionary computing, 13-30, 2001. [Google Scholar]
- M. Ionita, M. Breaban, C. Croitoru, New Achievements in Evolutionary Computation 17, (2010) [Google Scholar]
- N. Sakamoto, Y. Akimoto, Adaptive ranking based constraint handling for explicitly constrained black-box optimization, in Proceedings of the Genetic and Evolutionary Computation Conference, 700–708 (2019) [Google Scholar]
- H. Kanoh, M. Matsumoto, K. Hasegawa, N. Kato, S. Nishihara, Engineering Applications of Artificial Intelligence 10(6), 531–537 (1997) [CrossRef] [Google Scholar]
- J. Liu, W. Zhong, L. Jiao, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 36(1), 54–73 (2006) [CrossRef] [Google Scholar]
- O. Kramer, Applied Computational Intelligence and Soft Computing 2010, 1–19, (2010) [Google Scholar]
- V.H. Cantú, C. Azzaro-Pantel, A. Ponsich, Applied Soft Computing 108, 107442, (2021) [Google Scholar]
- J. Lampinen, A constraint handling approach for the differential evolution algorithm, in Proceedings of the 2002 Congress on Evolutionary Computation, CEC'02 (Cat. No. 02TH8600) 2 (2002) [Google Scholar]
- M. Breaban, M. Ionita, C. Croitoru, A new PSO approach to constraint satisfaction, in 2007 IEEE Congress on Evolutionary Computation, 1948-1954, (2007) [Google Scholar]
- I. Lin, Particle swarm optimization for solving constraint satisfaction problems, Master’s thesis, Simon Fraser Univ. (2005) [Google Scholar]
- B.G. Craenen, A.E. Eiben, IEEE Congress on Evolutionary Computation 3, 1922–1928, (2005) [Google Scholar]
- X. Ma, X. Li, Q. Zhang, K. Tang, Z. Liang, W. Xie, Z. Zhu, IEEE Transactions on Evolutionary Computation 23(3), 421–441 (2018) [Google Scholar]
- A. Vakhnin, E. Sopov, Algorithms 14(146) (2021) [Google Scholar]
- R. Tanabe, A. Fukunaga, Success-history based parameter adaptation for differential evolution, In 2013 IEEE congress on evolutionary computation, 71–78, (2013) [Google Scholar]
- G. Wu, R. Mallipeddi, P.N. Suganthan, Problem definitions and evaluation criteria for the CEC 2017 competition on constrained real-parameter optimization, Technical Report (2017) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.