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The design of a rolling system is a multistage process optimization problem involving sequential relationship between consecutive stages. This relationship is peculiar to sequential processes in which the output stock of one stage serves as the input stock into the deforming tool of the other stage. This paper describes the optimization of a real-life rolling system design using a genetic algorithm (GA)-based approach capable of dealing with the sequential nature of this problem. It presents a mathematical model of a real-life rolling system design and explains the proposed optimization approach. Even in the presence of multiple stages, the proposed approach identifies a variety of near-optimal design solutions from which one could be finally chosen based on designer's preferences. It is also shown that the obtained solutions dominate the designs reported in literature.