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Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| Harmony Search× | Simulated Annealing – Probabilistisk Optimering× | |
|---|---|---|
| Ämnesområde | Optimering | Optimering |
| Familj | Process / pipeline | Process / pipeline |
| Ursprungsår≠ | 2001 | 1983 |
| Upphovsperson≠ | Zong Woo Geem, Joong Hoon Kim, G. V. Loganathan | — |
| Typ≠ | Metaheuristic population-based optimization | Probabilistic metaheuristic / local search |
| Ursprungskälla≠ | 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 ↗ |
| Alias | HS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization | Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search |
| Närliggande | 5 | 5 |
| Sammanfattning≠ | 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. |
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