A genetic algorithm approach to hot strip mill rolling scheduling problems

Abstract

The operation of hot strip mill rolling scheduling (HSMRS) at China Steel Corporation (CSC), Taiwan is an extremely difficult and time consuming process due to the complexity of the problem. The paper explores how this problem can be solved through the use of a genetic algorithm. One of the key aspects of this approach is the use of specially designed representations for such scheduling problems. The representations explicitly encode a schedule by encoding information for building cycles. We have found that this representation cooperates with a stochastic violation directed mutation operator and suitable fitness function and can quickly produce results comparable to human scheduling. The efficient and flexible GA approach presented is potentially widely useful in other similar rolling cycle scheduling applications in large steel companies.