So sánh phương pháp

	Tối ưu hóa bầy đàn cho kịch bản chính sách	Tối ưu hóa Bầy đàn Hạt Ngẫu nhiên
Lĩnh vực	Mô phỏng	Mô phỏng
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1995 (PSO); applied to policy scenarios from 2000s onward	1995–2002
Người khởi xướng	Kennedy, J. & Eberhart, R. (PSO); policy scenario framing from planning and operations research literature	Kennedy, J. and Eberhart, R. (base PSO); stochastic extensions by Clerc, Kennedy and community
Loại	Metaheuristic optimization within policy scenario framework	Metaheuristic optimization — stochastic swarm intelligence
Công trình gốc	Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia, pp. 1942–1948.	Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95 - International Conference on Neural Networks, Vol. 4, pp. 1942-1948. IEEE.
Tên gọi khác	PS-PSO, Policy PSO, Scenario-based PSO, Policy scenario swarm optimization	Stochastic PSO, SPSO, Randomized PSO, Probabilistic PSO
Liên quan	6	4
Tóm tắt	Policy Scenario Particle Swarm Optimization integrates Particle Swarm Optimization (PSO) with explicit policy scenario analysis. A swarm of candidate policy solutions is evaluated under multiple defined future scenarios, and PSO's velocity-position update rules guide the swarm toward solutions that perform well—or robustly—across all considered scenarios. It is used in energy, environmental, infrastructure, and public resource planning.	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.