Process / pipelineSimulation / optimization
稳健遗传算法 — 不确定性下的演化优化
稳健遗传算法（RGA）扩展了标准遗传算法，旨在寻找不仅在标称设计点表现良好，而且在决策变量、参数或适应度评估中存在不确定性时也能表现良好的解决方案。通过将明确的稳健性度量纳入选择压力，RGA 在最优性与对扰动的敏感性之间取得了平衡，使其适用于现实世界变异性下的工程设计、调度和策略优化。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Jin, Y., Branke, J. (2005). Evolutionary optimization in uncertain environments — a survey. IEEE Transactions on Evolutionary Computation, 9(3), 303–317. DOI: 10.1109/TEVC.2005.846356 ↗
- Beyer, H.-G., Sendhoff, B. (2007). Robust optimization — A comprehensive survey. Computer Methods in Applied Mechanics and Engineering, 196(33–34), 3190–3218. DOI: 10.1016/j.cma.2007.03.003 ↗
如何引用本页
ScholarGate. (2026, June 3). Robust Genetic Algorithm — Evolutionary Optimization under Uncertainty. ScholarGate. https://scholargate.app/zh/simulation/robust-genetic-algorithm
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 遗传算法优化↔ compare
- 多目标遗传算法 (MOGA)仿真↔ compare
- 鲁棒多目标优化仿真↔ compare
- 鲁棒粒子群优化仿真↔ compare
- 鲁棒模拟退火仿真↔ compare
- 随机遗传算法仿真↔ compare