Two-machine flowshop scheduling with supportive constraints

This paper investigates a two-machine flowshop scheduling problem modeled from a real production context of a chemical factory that produces foam-related products. The operations are categorized as supportive items and regular jobs. Many different compositions of foam can be mixed at the foam blowing stage, and products are processed at the manufacturing stage. Each job on machine two cannot start until all of its supportive operations on machine one are finished. The problem is to determine a schedule whose total job completion time is minimum. We propose a branch and bound algorithm, a simple heuristic and a meta-heuristic ILS. Computational experiments are conducted to study the performances of the proposed algorithms.