方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Harmony Search× | 模拟退火× | |
|---|---|---|
| 领域 | 优化 | 优化 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2001 | 1983 |
| 提出者≠ | Zong Woo Geem, Joong Hoon Kim, G. V. Loganathan | — |
| 类型≠ | Metaheuristic population-based optimization | Probabilistic metaheuristic / local search |
| 开创性文献≠ | Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗ | Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗ |
| 别名 | HS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization | Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search |
| 相关 | 5 | 5 |
| 摘要≠ | Harmony Search (HS) is a population-based metaheuristic optimization algorithm introduced by Geem, Kim, and Loganathan in 2001. It mimics the improvisation process of jazz musicians seeking a perfect state of harmony, using three operators — memory consideration, pitch adjustment, and random selection — to generate candidate solutions. The algorithm applies to both continuous and discrete variables and has found wide use in engineering design, water distribution network optimization, and combinatorial problems. | 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. |
| ScholarGate数据集 ↗ |
|
|