A new Coordination Heuristic for Plant-wide Planning and Scheduling

Abstract

Abstract The work is motivated by a large-scale steel making process that consists of a meltshop as the first production section and a hot rolling mill as the second production section. The first section produces intermediate products (steel slabs in different quality) which can be stored in an intermediate storage (a slab yard) and which are consumed by the second section. Production planning for each of the sections constitutes a difficult multi-stage scheduling problem, these are currently solved independently. In this paper approaches to the coordination of the formerly uncoordinated schedulers are discussed. The objective is to reduce the lead time of stored intermediates. Shortening the lead time can significantly reduce the energy consumption since the hot slabs produced by the melt shop cool down over time and need to be reheated for the hot rolling mill, consuming large amounts of natural gas. A generic model formulation for batch schedule coordination problems is presented. The model is based on due date / release date constraints for each set of slabs. Three different algorithms to optimize the due / release dates such that the storage times of intermediates are minimized are discussed and compared: an algorithm based on Lagrangean decomposition, the black box algorithm MCS and a new coordination heuristic. The comparison shows the advantage of the proposed heuristic in terms of solution quality and computational effort. At the end the problems encountered when applying Lagrangean decomposition techniques to the scheduling coordination problem when the objective function is piecewise linear are discussed.