The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Pareto-, Aggregation-, and Indicator-Based Methods in Many-Objective Optimization
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Citations
Cites
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,796
Multi-Objective Optimization Using Evolutionary Algorithms
Deb, K., & Kalyanmoy, D. (2001) · Andalas University Repository (Andalas University) · Cited by 14,918
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,525
Evolutionary Algorithms for Solving Multi-Objective Problems
(2007) · Genetic and Evolutionary Computation Series · doi:10.1007/978-0-387-36797-2 · Cited by 5,686
SPEA2: Improving the strength pareto evolutionary algorithm
Zitzler, E., Laumanns, M., & Thiele, L. (2001) · doi:10.3929/ethz-a-004284029 · Cited by 5,008
Completely Derandomized Self-Adaptation in Evolution Strategies
Hansen, N., & Ostermeier, A. (2001) · Evolutionary Computation · doi:10.1162/106365601750190398 · Cited by 4,397
Evolutionary Algorithms for Solving Multi-Objective Problems
Coello Coello, C. A., Van Veldhuizen, D. A., & Lamont, G. B. (2002) · Genetic Algorithms and Evolutionary Computation · doi:10.1007/978-1-4757-5184-0 · Cited by 2,663
Multiobjective optimization using evolutionary algorithms — A comparative case study
Zitzler, E., & Thiele, L. (1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0056872 · Cited by 2,262
Indicator-Based Selection in Multiobjective Search
Zitzler, E., & Künzli, S. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30217-9_84 · Cited by 2,259
Cited by
HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization
Bader, J., & Zitzler, E. (2011) · Evolutionary Computation · doi:10.1162/evco_a_00009 · Cited by 2,081
Evolutionary many-objective optimization: A short review
Ishibuchi, H., Tsukamoto, N., & Nojima, Y. (2008) · 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) · doi:10.1109/cec.2008.4631121 · Cited by 914
A Grid-Based Evolutionary Algorithm for Many-Objective Optimization
Yang, S., Li, M., Liu, X., & Zheng, J. (2013) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2012.2227145 · Cited by 893
Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework
Hadka, D., & Reed, P. (2013) · Evolutionary Computation · doi:10.1162/evco_a_00075 · Cited by 717
Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes
Ishibuchi, H., Setoguchi, Y., Masuda, H., & Nojima, Y. (2017) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2016.2587749 · Cited by 592
Metadata
- Authors
- Wagner, T., Beume, N., & Naujoks, B.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2007-05-19
- Pages
- 742-756
- OpenAlex
- W1605170913
- Cited by
- 425
- References
- 25
- FWCI
- 22.02
- Type
- conference paper
- Language
- en
- Open access
- green
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- Wagner, T., Beume, N., & Naujoks, B. (2007). Pareto-, Aggregation-, and Indicator-Based Methods in Many-Objective Optimization. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-540-70928-2_56
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
