方法证据记录
Bayesian NSGA-II
Bayesian NSGA-II integrates Gaussian process surrogate models (Bayesian metamodels) into the NSGA-II evolutionary loop to solve expensive multi-objective optimization problems. By replacing costly true function evaluations with fast probabilistic predictions, it discovers high-quality Pareto-front approximations with far fewer real evaluations than standard NSGA-II.
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。
Bayesian Surrogate-Assisted 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
- Emmerich, M. T. M., Giannakoglou, K. C., Naujoks, B. (2006). Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels. IEEE Transactions on Evolutionary Computation, 10(4), 421–439. · DOI 10.1109/TEVC.2005.859463
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