'Institute of Electrical and Electronics Engineers (IEEE)'
Abstract
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 literatu
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