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This study explores the impact of vertical and horizontal configurations on thermal insulation in cellular concrete brick design, aiming to identify optimal insulation patterns. Results indicate that under a constant volume (67%) of coconut fiber, appropriate geometric changes can reduce thermal conductivity by around 10% (from 0.198 W/(m·K) to 0.178 W/(m·K)). Bayesian inference is employed to construct a bi-directional network, providing a more intuitive understanding of variable relationships. A probabilistic-driven search space reduction approach is proposed, improving candidate selection efficiency and reducing the number of assessments. The study introduces a Bayesian Genetic Algorithm (BGA), which outperforms the genetic algorithm when the mutation rate is 0.1.