方法证据记录
Bayesian Ant Colony Optimization
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Ant Colony Optimization — ACO with Bayesian probabilistic parameter learning
分类方法记录 · process-pipeline / simulation
- 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 10.1109/3477.484436
- Ant colony optimization algorithms. Wikipedia. · URL
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