A Comprehensive Optimization Model for Iron Transportation Scheduling under the ‘Large Cycle Mode’

In order to further improve the turnover rate of mixing iron engines, a comprehensive optimization model of molten iron transportation scheduling plan under the ‘Large Cycle Mode’ was studied based on the theory of constrained program cumulative scheduling and dictionary order multi-objective optimization. The first stage focuses on implementing tap plans, considering factors such as blast furnace operation sequence, molten iron tank operation logic, limited operation times of engines, time limit of molten iron cooling, and uniqueness of operation implementation. Based on the 2+1 and 2+2 tank distribution mode, the operation scheduling model of the first stage was established. Secondly, the resource allocation model was established by taking the maximum number of operation tasks completed by the engine as the second goal, and the task time sequence obtained in the first stage was assigned to the engine after ordering, and the resource allocation model was established with the constraints such as the uniqueness of the implementation of the engine transfer operation, the timing of the engine transfer operation, the priority of the connection of the task of the transfer operation, and the upper limit of the transfer operation. By integrating constraints from both stages and prioritizing minimal turnover rate, we formulate an optimization model. This model is solved iteratively using a hybrid algorithm of constrained propagation and multipoint constructive search. Simulation results demonstrate a 13.33% improvement in optimization outcomes compared to random restart algorithms, with a 70.58% increase in solution time efficiency. Furthermore, the turnover rate of mixing iron engines in the 2+1 versus 2+2 mode saw a 13.33% increase.