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In order to solve the dynamic scheduling problem of steelmaking and continuous casting, an improved differential evolution algorithm is proposed, which combines Lagrangian interpolation algorithm and differential evolution algorithm. The improved differential evolution algorithm adjusts the evolution parameters dynamically, dynamically adjusts the direction of differential evolution, and combines Lagrangian interpolation to optimize the local search ability of the differential evolution algorithm, and introduces weight coefficients to balance the global search and the local search. An experimental model is established based on the actual production data of a large domestic steel plant, with the goal of minimizing the total completion time, minimizing the total pouring interruption time, minimizing the total waiting time between heats, and minimizing the total deviation time. The evolutionary algorithm is applied to solve the dynamic disturbance event scheduling problem of steelmaking-continuous casting converter failure. The experimental results show that the improved differential evolution algorithm is applied to the steelmaking-continuous casting dynamic scheduling problem, which effectively shortens the total completion of the heat processing. Time, total waiting time between heats, and total pouring interruption time, within a reasonable range, effectively control the time deviation between the new production scheduling plan and the original scheduling plan, and avoid the continuous casting machine due to the occurrence of disturbance events.