ABSTRACT
This chapter proposes hybrid EAs with integration of GA and extremal optimization (EO) to solve a typical sequence-dependent scheduling problem, which is illustrated with the production scheduling of a hot-strip mill (HSM) in the steel industry. An HSM produces hot-rolled products from steel slabs, and is one of the most important production lines in an integrated mill or minimill. To make a manufacturing enterprise more competitive and profitable in the global marketplace, the profit-driven “make-to-order” or “make-to-stock” business model has been applied widely in manufacturing management. Among multidimensional business and production decisions, computer-aided production planning and scheduling to optimize desired business objectives subject to multiple sophisticated constraints has been one of the most important decisions. Standard GA applications use binary strings or ordinal integers to represent a chromosome of a solution. In the HSM-scheduling problem, we define the chromosome with a chain of genes as a rolling round.
