A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization
Liu J, Liu Y, Jin Y, Li F (2022)
IEEE Transactions on Systems, Man, and Cybernetics: Systems 52(5): 3360-3375.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Liu, Jianchang;
Liu, Yuanchao;
Jin, YaochuUniBi
;
Li, Fei
![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
Abstract / Bemerkung
Dominance robustness (DR) has been proposed for assessing the ability of the Pareto-optimal solutions to remain to be nondominated when the decision variables are subject to noise. There are two main challenges in search for dominance robust optimal solutions in dominance robust multiobjective optimization (MOP), namely, accurate estimation of the DR measure and a good balance between convergence and DR in the presence of uncertainty. In this article, a novel robust MOP evolutionary algorithm based on decision variable assortment (DVA) is proposed to tackle these challenges. To be specific, an indicator, termed as dominance robust indicator, is proposed to measure the DR based on the dominance level and dominance relationship of the sampled points. Then, the decision variables are divided into low DR-related variables and high DR-related variables based on the DVA strategy. Finally, low and high DR related variables are optimized separately to obtain the dominance robust optimal solutions. In addition, performance indicators to quantify the performance of dominance robust optimal solution set obtained by robust MOP algorithm are proposed. Experimental results have demonstrated that the proposed algorithm is competitive in search for dominance robust optimal solutions.
Erscheinungsjahr
2022
Zeitschriftentitel
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Band
52
Ausgabe
5
Seite(n)
3360-3375
ISSN
2168-2216
eISSN
2168-2232
Page URI
https://pub.uni-bielefeld.de/record/2978340
Zitieren
Liu J, Liu Y, Jin Y, Li F. A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2022;52(5):3360-3375.
Liu, J., Liu, Y., Jin, Y., & Li, F. (2022). A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(5), 3360-3375. https://doi.org/10.1109/TSMC.2021.3067785
Liu, Jianchang, Liu, Yuanchao, Jin, Yaochu, and Li, Fei. 2022. “A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization”. IEEE Transactions on Systems, Man, and Cybernetics: Systems 52 (5): 3360-3375.
Liu, J., Liu, Y., Jin, Y., and Li, F. (2022). A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems 52, 3360-3375.
Liu, J., et al., 2022. A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(5), p 3360-3375.
J. Liu, et al., “A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, 2022, pp. 3360-3375.
Liu, J., Liu, Y., Jin, Y., Li, F.: A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 52, 3360-3375 (2022).
Liu, Jianchang, Liu, Yuanchao, Jin, Yaochu, and Li, Fei. “A Decision Variable Assortment-Based Evolutionary Algorithm for Dominance Robust Multiobjective Optimization”. IEEE Transactions on Systems, Man, and Cybernetics: Systems 52.5 (2022): 3360-3375.