To simultaneously reduce automobile exhaust pollution to the environment and satisfy the demand for high-quality gasoline, the treatment of fluid catalytic cracking (FCC) gasoline is urgently needed to minimize octane number (RON) loss. We presented a new systematic method for determining an optimal operation scheme for minimising RON loss and operational risks. Firstly, many data were collected and preprocessed. Then, grey correlative degree analysis and Pearson correlation analysis were used to reduce the dimensionality, and the major variables with representativeness and independence were selected from the 367 variables. Then, the RON and sulfur (S) content were predicted by multiple nonlinear regression. A multi-objective nonlinear optimization model was established with the maximum reduction in RON loss and minimum operational risk as the objective function. Finally, the optimal operation scheme of the operating variable corresponding to the sample with a RON loss reduction greater than 30% in 325 samples was solved in Python.

Abstract

This study formulates a model to solve the scheduling problem of underway replenishment of naval battle group. First, an analogy is made between the underway replenishment scheduling project of naval battle group (URSP) and vehicle scheduling Problem (VSP). Then the impact factors to URSP based on the analysis of the similarity and difference between URSP and VSP are figured out and analyzed. The model of URSP is described, and its parameters are analyzed, and the quantitative approaches are given. The heuristic approach is provided to solve URSP, and an example is used to validate its feasibility, then the replenishment sequence is worked out. The result indicates that the model and the heuristic approach can be used to solve the URSP with complex constraints well, the result can be used as the support of decision-making.