TY - CHAP A1 - Davendra, Donald A1 - Herrmann, Frank A1 - Bialic-Davendra, Magdalena T1 - Scheduling tardiness constrained flow shop with simultaneously loaded stations using Genetic Algorithm T2 - Proceedings of the 4th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI 2020): Thimphu, Kingdom of Bhutan during March 21-22, 2020 N2 - 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. KW - simulation of restrictions KW - scheduling, KW - flow-shop KW - no-buffer (blocking) KW - no-wait KW - genetic algorithm KW - real world application KW - Ablaufplanung KW - Hierarchische Produktionsplanung KW - Flow-shop-Problem KW - Reihenfolgeproblem KW - Genetischer Algorithmus Y1 - 2020 U6 - https://doi.org/10.1145/3396474.3396475 PB - ACM ER - TY - CHAP A1 - Herrmann, Frank T1 - Genetic algorithm with simulation for scheduling of a flow shop with simultaneously loaded stations T2 - Proceedings of the 28th EUROPEAN Conference on Modeling and Simulation, May 27th - 30th, 2014, Brescia, Italy N2 - 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. Proceedings 28th European Conference on Modelling and Simulation. KW - Ablaufplanung KW - Hierarchische Produktionsplanung KW - Flow-shop-Problem KW - Reihenfolgeproblem KW - Genetischer Algorithmus KW - simulation of restrictions KW - scheduling KW - flow-shop KW - no-buffer (blocking) KW - no-wait KW - genetic algorithm KW - real world application Y1 - 2014 UR - http://www.scs-europe.net/dlib/2014/ecms14papers/simo_ECMS2014_0076.pdf ER -