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This document discusses the enhancement of the Bayesian Optimization Algorithm (BOA) by incorporating fitness inheritance to improve evaluation efficiency in complex real-world problems. It outlines the methodology for extending Bayesian networks to include fitness information and presents experimental results demonstrating significant speed-ups in solution evaluation. The findings indicate that high proportions of inherited fitness information lead to optimal performance improvements, particularly in challenging optimization scenarios.




















