Módszerek összehasonlítása

	Bayes-féle Részecske-raj Optimalizálás	Bayes-féle Genetikus Algoritmus
Tudományterület	Szimuláció	Szimuláció
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	2003	1999
Megalkotó	Higashi, N., Iba, H. (extending Kennedy and Eberhart's PSO)	Pelikan, M., Goldberg, D. E., & Cantu-Paz, E.
Típus	Hybrid metaheuristic — Bayesian probabilistic swarm search	Evolutionary metaheuristic with Bayesian probabilistic model
Alapmű	Higashi, N., Iba, H. (2003). Particle swarm optimization with Gaussian mutation. Proceedings of the 2003 IEEE Swarm Intelligence Symposium, Indianapolis, IN, USA, pp. 72-79.	Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. (1999). BOA: The Bayesian optimization algorithm. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-1999), pp. 525–532. Morgan Kaufmann.
Alternatív nevek	Bayesian PSO, BPSO, Probabilistic Swarm Optimization, Prior-guided PSO	BGA, Bayesian-guided GA, Probabilistic GA, EDA-GA
Kapcsolódó	6	5
Összefoglaló	Bayesian Particle Swarm Optimization (Bayesian PSO) integrates Bayesian probabilistic reasoning into the standard particle swarm framework. Particles update their velocities and positions guided not only by personal and global best positions but also by a Bayesian posterior that encodes prior knowledge about the solution space, enabling more directed and statistically principled exploration of complex optimization landscapes.	A Bayesian Genetic Algorithm (BGA) replaces traditional crossover and mutation operators with a probabilistic Bayesian network learned from selected high-fitness individuals. At each generation the algorithm builds a graphical model of promising solution structure, then samples new offspring from that model, enabling the search to capture and exploit variable dependencies that standard GAs miss.