Even though research in flow shop production scheduling has been carried out for many decades,there is still a gap between research and application especially in manufacturing paradigms such as one-of-a-kind production(OKP) that intensely challenges realtime adaptive production scheduling and control.Indeed,many of the most popular heuristics continue to use Johnson’s algorithm(1954) as their
core. This paper presents a state space(SS)heuristic,integrated with a closed-loop feedback control structure,to achieve adaptive production scheduling and control in OKP. Our (SS) heuristic,because of its simplicity and computational efficiency,has the potential to become a core heuristic.Through a series of case studies,including an industrial implementation in OKP,our SS-based production scheduling and
control system demonstrates significant potential to improve production efficiency.