Process / pipeline
差分进化 — 全局随机优化器
差分进化（DE）由Rainer Storn和Kenneth Price于1997年提出，是一种基于种群的随机优化算法，专为连续参数空间设计。它通过组合现有种群成员的向量差来生成候选解，使其成为非凸、多峰或不适合基于梯度方法的搜索地形的强大且参数精简的遗传算法和粒子群优化算法的替代方案。
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Method map
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来源
- Storn, R. & Price, K. (1997). Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, 11(4), 341–359. DOI: 10.1023/A:1008202821328 ↗
- Das, S., Mullick, S. S., & Suganthan, P. N. (2016). Recent advances in differential evolution – An updated survey. Swarm and Evolutionary Computation, 27, 1–30. DOI: 10.1016/j.swevo.2016.01.004 ↗
如何引用本页
ScholarGate. (2026, June 1). Differential Evolution (DE). ScholarGate. https://scholargate.app/zh/optimization/differential-evolution
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.
- Bayesian Regression贝叶斯↔ compare
- 深度强化学习深度学习↔ compare
- 遗传算法优化↔ compare
- 神经架构搜索深度学习↔ compare
- 主成分分析机器学习↔ compare