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Flower pollination algorithm: A novel approach for multiobjective optimization
Open accessAbstract
Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this article, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems. The proposed method is used to solve a set of multiobjective test functions and two bi-objective design benchmarks, and a comparison of the proposed algorithm with other algorithms has been made, which shows that the FPA is efficient with a good convergence rate. Finally, the importance for further parametric studies and theoretical analysis is highlighted and discussed.
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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
MOEA/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
Cited by
Bio inspired computing – A review of algorithms and scope of applications
Kar, A. K. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.04.018 · Cited by 578
Hu, Y., Qin, L., Li, S., Li, X., Zhou, R., Li, Y., & Sheng, W. (2023) · Energy and Buildings · doi:10.1016/j.enbuild.2023.113429 · Cited by 22
Metadata
- Authors
- Yang, X.-S., Karamanoglu, M., & He, X.
- Venue
- Engineering Optimization
- Publisher
- Informa UK Limited
- Published
- 2013-10-04
- Volume
- 46
- Issue
- 9
- Pages
- 1222-1237
- ISSN
- 0305-215X (ISSN-L)
- 1029-0273
- OpenAlex
- W2146439308
- Cited by
- 629
- References
- 2
- FWCI
- 27.26
- Type
- journal article
- Language
- en
- Open access
- green
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