Process / pipelineSimulation / optimization
贝叶斯NSGA-II — 代理辅助多目标进化优化
贝叶斯NSGA-II 将高斯过程代理模型（贝叶斯元模型）集成到NSGA-II进化循环中，以解决计算成本高昂的多目标优化问题。通过用快速的概率预测替代昂贵的真实函数评估，它能以远少于标准NSGA-II的真实评估次数发现高质量的帕累托前沿近似。
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来源
- 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 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Surrogate-Assisted Non-dominated Sorting Genetic Algorithm II. ScholarGate. https://scholargate.app/zh/simulation/bayesian-nsga-ii
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