The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Push and pull search for solving constrained multi-objective optimization problems
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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
Self-citationMOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Zhang, Q., & Li, H. (2007) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2007.892759 · Cited by 10,069
Self-citationMultiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Zitzler, E., & Thiele, L. (1999) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.797969 · Cited by 8,798
An efficient constraint handling method for genetic algorithms
Deb, K. (2000) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/s0045-7825(99)00389-8 · Cited by 3,892
Self-citationCoello Coello, C. A. (2002) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/s0045-7825(01)00323-1 · Cited by 2,343
Jain, H., & Deb, K. (2014) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2013.2281534 · Cited by 2,172
Self-citationStochastic ranking for constrained evolutionary optimization
Runarsson, T. P., & Yao, X. (2000) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.873238 · Cited by 1,807
The balance between proximity and diversity in multiobjective evolutionary algorithms
Bosman, P. A. N., & Thierens, D. (2003) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2003.810761 · Cited by 1,154
Constraint-handling in nature-inspired numerical optimization: Past, present and future
Mezura-Montes, E., & Coello Coello, C. A. (2011) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2011.10.001 · Cited by 1,127
Many-Objective Evolutionary Algorithms: A Survey
Li, B., Li, J., Tang, K., & Yao, X. (2015) · ACM Computing Surveys · doi:10.1145/2792984 · Cited by 815
Cited by
Liu, Z.-Z., & Wang, Y. (2019) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2019.2894743 · Cited by 486
Zhao, R., Tao, S., & Li, P. (2025) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2024.102942 · Cited by 22
Metadata
- Authors
- Fan, Z., Li, W., Cai, X., Li, H., Wei, C., Zhang, Q., Deb, K., & Goodman, E.
- Venue
- Swarm and Evolutionary Computation
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 44
- Pages
- 665-679
- ISSN
- 2210-6502 (ISSN-L)
- OpenAlex
- W2963115819
- Cited by
- 594
- References
- 26
- FWCI
- 14.91
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Fan, Z., Li, W., Cai, X., Li, H., Wei, C., Zhang, Q., Deb, K., & Goodman, E. (2019). Push and pull search for solving constrained multi-objective optimization problems. Swarm and Evolutionary Computation. https://doi.org/10.1016/j.swevo.2018.08.017
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
