Dynamic flexible flow shop problems—Scheduling heuristics vs. autonomous control

Flexible flow shop problems are well known and common tasks. Two practice-oriented extensions are unrelated parallel machines on the one hand and dynamic aspects in terms of distributed release times on the other hand. Triggered by the growing complexity of logistics systems, the paradigm of central planning is being shifted to decentralized autonomous control. This work focuses on two different autonomous control methods applied to flexible flow shop problems with both of the extensions mentioned above. In order to evaluate these methods, various common scheduling heuristics and one genetic algorithm are taken as references. Problem instances are defined and solved by autonomous control and the reference algorithms. The results of this evaluation are shown and discussed.