To address the limitation of existing reliability analysis methods that focus solely on the topological structure of communication networks while neglecting 5G/ B5G ( 5th Generation and Beyond 5th Generation Mobile Communication Technology) channel characteristics, a communication network optimization platform is developed based on the reliability of the multi-state flow network. The path loss, shadow fading and inter-channel correlation parameters of the wireless channel are introduced to construct the link reliability of the multi-state flow network. A recursive Monte Carlo algorithm enhanced with two heuristic rules is proposed to improve reliability accuracy and computational efficiency by reducing simulation iterations and minimizing path sets. Utilizing a front-end and back-end separated architecture implemented in Java, the developed platform supports dual topology construction methods, drag-and-drop component assembly and one-click import functionality. Network reliability and end-to-end reliability metrics derived from the proposed algorithm can be generated through single-click operation. Experimental results show that the proposed method converges quickly and has high accuracy in solving the reliability of large-scale networks. The developed platform has a friendly human-computer interaction interface. It is simple and fast to generate network topology and obtain network reliability. The reliability generated by the platform has a certain guiding role in the optimization of multi-state communication networks.