| Summary: | Research on heterogeneous combat networks (HCNs) has attracted considerable interest in the military field since they can provide useful insights into the provision of decision-making assistance. The characteristics of high-operational-capability HCNs are not well studied, which limits the ability to construct a better combat network. To fill this gap, an integrated methodology named genetic algorithm-based high-capability HCN analysis (GAHCA) is presented to elucidate the characteristics of high-operational-capability combat networks. In GAHCA, an improved genetic algorithm is proposed to search more efficiently for high-operational-capability HCNs. Then, the properties of these HCNs are studied by the cartographic picture analysis and contribution analysis of nodes and links. The results unveil the critical topological structures of operational capability generation and quantitatively demonstrate the importance of the military criterion of “concentration of superior forces”. These results further emphasize that blindly increasing military resources may not enhance the operational capability of the HCN and, worse yet, may instead cause a decrease in network capability. These are all meaningful findings for assisting in the construction of a better HCN. Finally, the reliability of the improved genetic algorithm is demonstrated by comparison with two state-of-the-art algorithms and one classical algorithm.
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