The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II
Abstract
Partly due to lack of test problems, the impact of the Pareto set (PS) shapes on the performance of evolutionary algorithms has not yet attracted much attention. This paper introduces a general class of continuous multiobjective optimization test instances with arbitrary prescribed PS shapes, which could be used for studying the ability of multiobjective evolutionary algorithms for dealing with complicated PS shapes. It also proposes a new version of MOEA/D based on differential evolution (DE), i.e., MOEA/D-DE, and compares the proposed algorithm with NSGA-II with the same reproduction operators on the test instances introduced in this paper. The experimental results indicate that MOEA/D could significantly outperform NSGA-II on these test instances. It suggests that decomposition based multiobjective evolutionary algorithms are very promising in dealing with complicated PS shapes.
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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
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
Self-citation
Cited by
Differential Evolution: A Survey of the State-of-the-Art
Das, S., & Suganthan, P. N. (2011) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2010.2059031 · Cited by 5,307
Platemo: a matlab platform for evolutionary multi-objective optimization [educational forum]
Tian, Y., Cheng, R., Zhang, X., & Jin, Y. (2017) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2017.2742868 · Cited by 2,777
Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model
Zhang, Q., Liu, W., Tsang, E., & Virginas, B. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2033671 · Cited by 746
Self-citationThe performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances
Zhang, Q., Liu, W., & Li, H. (2009) · 2009 IEEE Congress on Evolutionary Computation · doi:10.1109/cec.2009.4982949 · Cited by 624
Self-citationMultiobjective firefly algorithm for continuous optimization
Yang, X.-S. (2013) · Engineering with Computers · doi:10.1007/s00366-012-0254-1 · Cited by 513
Metadata
- Authors
- Li, H., & Zhang, Q.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2009-04
- Volume
- 13
- Issue
- 2
- Pages
- 284-302
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2150046657
- Cited by
- 2,543
- References
- 2
- FWCI
- 43.55
- Type
- journal article
- Language
- en
- Open access
- closed
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- Li, H., & Zhang, Q. (2009). Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II. IEEE Transactions on Evolutionary Computation. https://doi.org/10.1109/tevc.2008.925798
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