This paper adopts equal relatively load as objective function, and makes every parameter to meet certain restrictive conditions. SUMT algorithm was used to change constraints to non-binding conditions. QPSO algorithm was applied to optimize objective functions to obtain optimal solution. This algorithm was based on classical particle swarm optimization, which, with the conduct of quantum particle, had effective global search capability, good convergence and stability. As a result, reasonable distribution of tandem cold rolling power and full use of equipment capacity were realized, resulting in the improvement of production efficiency.
Multi-Objective Optimization of Rolling Schedule for Five-Stand Tandem Cold Mill
