The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization
Abstract
Evolutionary algorithms have been shown to be powerful for solving multiobjective optimization problems, in which nondominated sorting is a widely adopted technique in selection. This technique, however, can be computationally expensive, especially when the number of individuals in the population becomes large. This is mainly because in most existing nondominated sorting algorithms, a solution needs to be compared with all other solutions before it can be assigned to a front. In this paper we propose a novel, computationally efficient approach to nondominated sorting, termed efficient nondominated sort (ENS). In ENS, a solution to be assigned to a front needs to be compared only with those that have already been assigned to a front, thereby avoiding many unnecessary dominance comparisons. Based on this new approach, two nondominated sorting algorithms have been suggested. Both theoretical analysis and empirical results show that the ENS-based sorting algorithms are computationally more efficient than the state-of-the-art nondominated sorting methods.
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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
Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
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An efficient constraint handling method for genetic algorithms
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Laumanns, M., Thiele, L., Deb, K., & Zitzler, E. (2002) · Evolutionary Computation · doi:10.1162/106365602760234108 · Cited by 1,487
PESA-II: region-based selection in evolutionary multiobjective optimization
Corne, D., Jerram, N. R., Knowles, J. D., & Oates, M. J. (2001) · Cited by 1,011
SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
Zitzler, E., Giannakoglou, K., Tsahalis, D., Periaux, J., Papailiou, K., (eds, T. F., Ler, E. Z., Laumanns, M., & Thiele, L. (2002) · Cited by 1,010
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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
Self-citationA Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization
Cheng, R., Jin, Y., Olhofer, M., & Sendhoff, B. (2016) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2016.2519378 · Cited by 1,760
Self-citationMultiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics
Zhang, C., Lim, P., Qin, A. K., & Tan, K. C. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2582798 · Cited by 870
Tian, Y., Cheng, R., Zhang, X., Cheng, F., & Jin, Y. (2018) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2017.2749619 · Cited by 699
Self-citationBinary differential evolution with self-learning for multi-objective feature selection
Zhang, Y., Gong, D.-W., Gao, X.-Z., Tian, T., & Sun, X.-Y. (2020) · Information Sciences · doi:10.1016/j.ins.2019.08.040 · Cited by 429
Metadata
- Authors
- Zhang, X., Tian, Y., Cheng, R., & Jin, Y.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2015-04
- Volume
- 19
- Issue
- 2
- Pages
- 201-213
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W1833634424
- Cited by
- 531
- References
- 14
- FWCI
- 40.19
- Type
- journal article
- Language
- en
- Open access
- closed
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