方法对比
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| 确定性模拟退火× | 模拟退火× | |
|---|---|---|
| 领域≠ | 仿真 | 优化 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990 | 1983 |
| 提出者≠ | Rose, K., Gurewitz, E., Fox, G. C. | — |
| 类型≠ | Deterministic metaheuristic — annealing schedule without probabilistic acceptance | Probabilistic metaheuristic / local search |
| 开创性文献≠ | Rose, K., Gurewitz, E., Fox, G. C. (1990). A deterministic annealing approach to clustering. Pattern Recognition Letters, 11(9), 589-594. DOI ↗ | Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗ |
| 别名≠ | DSA, Deterministic Annealing, Greedy Annealing, Temperature-Scheduled Descent | Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search |
| 相关≠ | 2 | 5 |
| 摘要≠ | Deterministic Simulated Annealing (DSA) is an optimization metaheuristic that adopts the cooling-schedule structure of classical simulated annealing but replaces the probabilistic Metropolis acceptance criterion with a strictly deterministic rule: only improving moves are accepted. This yields a reproducible, greedy-descent procedure guided by an annealing temperature schedule. | Simulated annealing is a probabilistic local-search metaheuristic introduced by Kirkpatrick, Gelatt, and Vecchi in 1983. It models the physical annealing process in metallurgy — where a material is heated and then slowly cooled to reach a low-energy crystalline state — and uses this analogy to escape local optima in combinatorial and continuous optimization problems. |
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