Ethylene production plants have great differences in terms of equipment, technology, and yields. Moreover, the production cost and carbon emission are closely related to the solution of feedstock scheduling. Therefore, how to choose a reasonable solution of feedstock scheduling is a great challenge for decision makers. Traditional modeling and selection strategies are involved with a large number of parameters and data. Fortunately, the superstructure base on process graph (P-Graph) is friendly to decision makers in both modeling and optimization. However, when the required solution is missing from the case base, the superstructure needs to be constructed and optimized again, which will consume a lot of resources and costs. To solve the above problems, this paper proposes a novel reasoning strategy based on extensible P-Graph. In the proposed methodology, P-Graph is regarded as the basic method of superstructure optimization. In the absence of available solutions, a reasoning strategy is integrated into extensible P-Graph to obtain new feedstock scheduling solutions. To verify the effectiveness of the proposed methodology, three cases of missing structural schemes, missing parameters and structural solutions, and missing target features are carried out. Simulation results indicate that the proposed methodology can provide a good solution selection strategy with decision makers, and the final required solution can be found. In addition, the burden of modeling and optimization can be greatly reduced.