The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Applications of multi-objective evolutionary algorithms in economics and finance: A survey
Abstract
This paper provides a state-of-the-art survey of applications of multi-objective evolutionary algorithms in economics and finance reported in the specialized literature. A taxonomy of applications within this area is proposed, and a brief review of the most representative research reported to date is then provided. In the final part of the paper, some potential paths for future research within this area are identified.
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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
Glover, F., & Laguna, M. (1997) · doi:10.1007/978-1-4615-6089-0 · Cited by 3,001
Cited by
A review of multi-objective optimization: Methods and its applications
Gunantara, N. (2018) · Cogent Engineering · doi:10.1080/23311916.2018.1502242 · Cited by 1,150
Metadata
- Authors
- Castillo Tapia, M. G., & Coello Coello, C. A.
- Venue
- 2007 IEEE Congress on Evolutionary Computation
- Publisher
- IEEE
- Published
- 2007-09
- Pages
- 532-539
- OpenAlex
- W2101008160
- Cited by
- 169
- References
- 2
- FWCI
- 4.19
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Applications of multi-objective evolutionary algorithms in economics and finance: A survey. https://app.cochat.ai/papers/10.1109/cec.2007.4424516
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- Castillo Tapia, M. G., & Coello Coello, C. A. (2007). Applications of multi-objective evolutionary algorithms in economics and finance: A survey. 2007 IEEE Congress on Evolutionary Computation. https://doi.org/10.1109/cec.2007.4424516
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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.
