Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Firefly Algoritme× | Harmony Search× | |
|---|---|---|
| Vakgebied | Optimalisatie | Optimalisatie |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | 2008 | 2001 |
| Grondlegger≠ | Xin-She Yang | Zong Woo Geem, Joong Hoon Kim, G. V. Loganathan |
| Type≠ | Swarm intelligence metaheuristic | Metaheuristic population-based optimization |
| Oorspronkelijke bron≠ | Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗ | Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗ |
| Aliassen | FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm) | HS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization |
| Verwant | 5 | 5 |
| Samenvatting≠ | The Firefly Algorithm (FA), introduced by Xin-She Yang in 2008 and formally published in 2010, is a nature-inspired swarm metaheuristic that models the bioluminescent attraction behaviour of fireflies. Each candidate solution is a firefly whose brightness represents its objective-function value; dimmer fireflies move toward brighter ones with an attraction force that decays with distance, driving the swarm toward optima without gradient information. | 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. |
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