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This paper establishes the models of the steelmaking continuous casting (SCC) process, and proposed the improved algorithms for this problem. The simulation results of a computerized scheduling system are also given to prove the model. The SCC process scheduling problem is very difficult to get a good performance solution in practice. The scheduling of the SCC process requires that each cast plan is processed on time, and the charges should be processed continuously for the same caster in the same cast, as well as the waiting time of the charges cannot be conflicted mutually in the same converters. We propose a quantum-behaved particle swarm optimization (QPSO) and improved algorithm strategy. The results show that the QPSO is very efficient for solving the SCC production scheduling problem, especially for large scale problem. (Received, processed and accepted by the Chinese Representative Office.)

Simulating Schedule Optimization Problem in Steelmaking Continuous Casting Process