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| Tối ưu hóa bầy kiến kiểu Bayes× | Thuật toán Di truyền Bayes× | |
|---|---|---|
| Lĩnh vực | Mô phỏng | Mô phỏng |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1996 (ACO); Bayesian variant: 2000s | 1999 |
| Người khởi xướng≠ | Dorigo, M. et al. (ACO); Bayesian extensions by multiple researchers in the 2000s–2010s | Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. |
| Loại≠ | Metaheuristic with Bayesian probabilistic learning | Evolutionary metaheuristic with Bayesian probabilistic model |
| Công trình gốc≠ | Dorigo, M., Maniezzo, V., Colorni, A. (1996). Ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 26(1), 29–41. DOI ↗ | 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. link ↗ |
| Tên gọi khác | BACO, Bayesian ACO, Bayesian-guided ACO, Probabilistic ACO | BGA, Bayesian-guided GA, Probabilistic GA, EDA-GA |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Bayesian Ant Colony Optimization (BACO) is a hybrid metaheuristic that embeds Bayesian inference into the Ant Colony Optimization framework. By treating pheromone intensities or algorithm parameters as probability distributions updated with collected evidence, BACO improves convergence reliability and robustness compared to classical ACO on noisy or uncertain combinatorial optimization problems. | 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. |
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