Genetic optimization of ladle scheduling in empty-ladle operation stage based on temperature drop control

To optimize ladle scheduling in the empty-ladle operation stage of steel plants, a mathematical scheduling model was established for the empty-ladle operation stage, taking the minimum total waiting time in the empty-ladle operation stage as the optimization goal and setting the equipment assignment uniqueness as the key constraint. An improved genetic algorithm was designed to calculate the mathematical scheduling model. In the operation of the genetic algorithm, the strategy of “ladle temperature drop control” was adopted to solve the problem of equipment conflicts and reduce unreasonable ladle temperature drops to enhance “red-ladle” utilization. Five main production modes operating at 95% capacity in a Chinese steel plant were simulated using the genetic optimization model. The results showed that the genetic optimization model could improve the efficiency of ladle operation and reduce the total waiting time in the empty-ladle operation stage by 868–1147 min.