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| Алгоритъм за оптимизация с китове (WOA)× | Оптимизация чрез рояк от частици (PSO)× | |
|---|---|---|
| Област | Оптимизация | Оптимизация |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2016 | 1995 |
| Създател≠ | Seyedali Mirjalili & Andrew Lewis | — |
| Тип≠ | Swarm-based metaheuristic | Population-based metaheuristic / swarm intelligence |
| Основополагащ източник≠ | Mirjalili, S. & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. DOI ↗ | Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗ |
| Други названия | WOA, Balina Optimizasyon Algoritması (WOA), bubble-net attacking method | PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO) |
| Свързани≠ | 5 | 6 |
| Резюме≠ | The Whale Optimization Algorithm (WOA) is a swarm-based metaheuristic introduced by Mirjalili and Lewis in 2016. It models the bubble-net hunting strategy of humpback whales, in which a group of whales spirals around prey while gradually tightening the encirclement. The algorithm balances global exploration and local exploitation through a small set of parameters and has become widely used in continuous engineering optimisation problems. | Particle Swarm Optimization (PSO) is a population-based metaheuristic algorithm introduced by Kennedy and Eberhart in 1995, inspired by the collective movement of bird flocks and fish schools. Each candidate solution — called a particle — moves through the search space by updating its velocity and position based on its own best experience and the best experience of the entire swarm, enabling fast convergence across continuous optimization problems. |
| ScholarGateНабор от данни ↗ |
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