方法证据记录
Robust NSGA-II
Robust NSGA-II extends the classic NSGA-II evolutionary algorithm to account for parametric uncertainty, finding Pareto-optimal trade-off solutions that remain high-performing even when input parameters deviate from their nominal values. Instead of optimizing objective values at a single point, it evaluates each candidate solution across a range or distribution of uncertainty realizations and selects for robustness alongside Pareto dominance.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Non-dominated Sorting Genetic Algorithm II
分类方法记录 · process-pipeline / simulation
- Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. · DOI 10.1109/4235.996017
- Deb, K., & Gupta, H. (2006). Introducing robustness in multi-objective optimization. Evolutionary Computation, 14(4), 463-494. · DOI 10.1162/evco.2006.14.4.463
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