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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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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