Process / pipelineSimulation / optimization
随机遗传算法 — 优化问题的随机进化搜索
随机遗传算法 (Stochastic Genetic Algorithm, SGA) 是一种基于群体的元启发式算法，它模仿生物进化过程——选择、交叉和变异——以在复杂、非线性或组合空间中搜索近优解。其随机算子使其对局部最优解具有鲁棒性，并广泛应用于工程、调度、机器学习和运筹学领域。
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Method map
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来源
- Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor. ISBN: 978-0262581110
- Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA. ISBN: 978-0201157673
如何引用本页
ScholarGate. (2026, June 3). Stochastic Genetic Algorithm — Randomized evolutionary search for combinatorial and continuous optimization. ScholarGate. https://scholargate.app/zh/simulation/stochastic-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.
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