The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Constrained multi-objective optimization algorithm with an ensemble of constraint handling methods
Abstract
Different constraint handling techniques have been used with multi-objective evolutionary algorithms (MOEA) to solve constrained multi-objective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of the parameter tuning. To overcome this selection problem, an ensemble of constraint handling methods (ECHM) is used to tackle constrained multi-objective optimization problems. The ECHM is integrated with a multi-objective differential evolution (MODE) algorithm. The performance is compared between the ECHM and the same single constraint handling methods using the same MODE (using codes available from http://www3.ntu.edu.sg/home/EPNSugan/index.htm). The results show that ECHM overall outperforms the single constraint handling methods.
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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
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No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
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
Self-citationPush and pull search for solving constrained multi-objective optimization problems
Fan, Z., Li, W., Cai, X., Li, H., Wei, C., Zhang, Q., Deb, K., & Goodman, E. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2018.08.017 · Cited by 594
Liu, Z.-Z., & Wang, Y. (2019) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2019.2894743 · Cited by 486
Difficulty Adjustable and Scalable Constrained Multiobjective Test Problem Toolkit
Fan, Z., Li, W., Cai, X., Li, H., Wei, C., Zhang, Q., Deb, K., & Goodman, E. (2020) · Evolutionary Computation · doi:10.1162/evco_a_00259 · Cited by 308
Ensemble strategies for population-based optimization algorithms – A survey
Wu, G., Mallipeddi, R., & Suganthan, P. N. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2018.08.015 · Cited by 270
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Metadata
- Authors
- Qu, B. Y., & Suganthan, P. N.
- Venue
- Engineering Optimization
- Publisher
- Informa UK Limited
- Published
- 2010-11-10
- Volume
- 43
- Issue
- 4
- Pages
- 403-416
- ISSN
- 0305-215X (ISSN-L)
- 1029-0273
- OpenAlex
- W2133738572
- Cited by
- 190
- References
- 3
- FWCI
- 9.39
- Type
- journal article
- Language
- en
- Open access
- closed
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