Optimization of hot rolled coil widths using a genetic algorithm

This paper focuses on the assortment problem in the steel industry; with the help of the genetic algorithm, it attempts to determine the optimum width of the parent stock given a set of forecasted customer widths so that the trim loss is minimized. For each given set of forecasted customer widths, an attempt is made to find a single width of the mother coil to be manufactured and kept in stock. In the genetic algorithm, six different selection schemes are considered. A number of test problems are taken up for different selection schemes. Evaluated against the maximum fitness value, the optimal mother coil width, and the generation number at which they are achieved, the elitism selection scheme shows consistently good results in all the test problems compared with the other selection mechanisms.