@inproceedings{DavendraHerrmannBialicDavendra, author = {Davendra, Donald and Herrmann, Frank and Bialic-Davendra, Magdalena}, title = {Scheduling tardiness constrained flow shop with simultaneously loaded stations using Genetic Algorithm}, series = {Proceedings of the 4th International Conference on Intelligent Systems, Metaheuristics \& Swarm Intelligence (ISMSI 2020): Thimphu, Kingdom of Bhutan during March 21-22, 2020}, booktitle = {Proceedings of the 4th International Conference on Intelligent Systems, Metaheuristics \& Swarm Intelligence (ISMSI 2020): Thimphu, Kingdom of Bhutan during March 21-22, 2020}, publisher = {ACM}, doi = {10.1145/3396474.3396475}, abstract = {In this study, a real world flow shop with a transportation restriction is regarded. This restriction reduces the set of feasible schedules even more than the no-buffer restrictions discussed in the literature in the case of limited storage. Still this problem is NP-hard. Since this scheduling problem is integrated in the usual hierarchical planning, the tardiness is minimised. Compared to even specific priority rule for this class of problems the suggested genetic algorithm delivers significant better results. The specific structure of this class of problems complicates the calculation of the performance criteria. This is solved by a simulation algorithm.}, subject = {Ablaufplanung}, language = {en} }