A Hybrid MIP–CP Approach to Multistage Scheduling Problem in Continuous Casting and Hot-Rolling Processes

This paper studies a new scheduling problem in a steel plant, referring to continuous casting (CC), reheating furnace, and hot rolling (HR) processes, which is meaningful and important to the production efficiency and energy saving. First, the problem is modeled as a combination of two coupled subproblems: one assigns casts to continuous casting (CC) machines, decides sequence and start time for casts and rolling units; and another assigns furnaces and decides start time for rolling slabs in a reheating furnace. The objectives are to maximize the number of slabs processed in a mode of hot charge rolling or direct hot charge rolling so as to reduce the energy requirement and the temperature drop of slabs and minimize the residence time of slabs in a reheating furnace to save energy. Then, based on a Benders decomposition strategy, a hybrid algorithm that combines mixed-integer programming and constraint programming is designed to solve each subproblem. An effective cut-generation scheme based on a priority relationship is developed for resolving resource conflicts and unsatisfied setup time constraints. Finally, extensive experiments are conducted to verify the effectiveness of the proposed approach. Note to Practitioners—This paper deals with a scheduling problem arising from CC to HR process in steel manufacturing. It decomposes the original problem into a CC–HR scheduling problem and a reheating furnace scheduling problem. Previously, such a problem is handled, respectively, which always cause energy waste and mismatching plan. This paper takes complex technology constraints into full account to minimize energy waste and energy requirement and establishes nonlinear mathematical models for studied problems. Then, it designs a hybrid algorithm combined mixed-integer programming and constraint programming. The results demonstrate that the proposed approach can solve them effectively. The obtained solution gives decision makers some desired reference to determine a right schedule when actual production tasks are executed.