A New Mixed Evolution Algorithm for Solving Steelmaking and Continuous Casting Scheduling Problem

The steelmaking continuous casting (SCC) is an important link in the steel production process, the appropriate SCC scheduling can help to improve the productive efficiency. Therefore, this paper studies the SCC scheduling problem (SCCSP), in which the average sojourn time, total weighted earliness and tardiness, and maximum completion time are taken as the objective functions. Firstly, a mixed-integer programming mathematical model of SCCSP is established according to the SCC production process. Secondly, a new mixed evolution algorithm (NMEA), which incorporates the crossover and mutation of differential evolution into the onlooker bee stage of discrete artificial bee colony algorithm to enhance search capability and balance the global and local search capabilities, is developed. Finally, the real experiment instances from a steel company are designed to evaluate the performance of NMEA. By comparing with other three high level algorithms, the NMEA gives better results for solving the SCCSP.