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| Tối ưu hóa Bầy đàn Hạt Ngẫu nhiên× | Tối ưu hóa Bầy đàn Hạt (PSO)× | |
|---|---|---|
| Lĩnh vực≠ | Mô phỏng | Tối ưu hóa |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1995–2002 | 1995 |
| Người khởi xướng≠ | Kennedy, J. and Eberhart, R. (base PSO); stochastic extensions by Clerc, Kennedy and community | — |
| Loại≠ | Metaheuristic optimization — stochastic swarm intelligence | Population-based metaheuristic / swarm intelligence |
| Công trình gốc≠ | Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95 - International Conference on Neural Networks, Vol. 4, pp. 1942-1948. IEEE. DOI ↗ | Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗ |
| Tên gọi khác≠ | Stochastic PSO, SPSO, Randomized PSO, Probabilistic PSO | PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO) |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | Stochastic Particle Swarm Optimization (Stochastic PSO) is a swarm-intelligence metaheuristic that extends the standard PSO framework by incorporating explicit stochastic elements — random inertia weights, probabilistic velocity resets, or noise injections — to escape local optima and maintain population diversity throughout the search. It is widely applied to continuous, mixed, and noisy optimization problems in engineering, operations research, and simulation-based design. | 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. |
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