Balancing and scheduling of flexible mixed model assembly lines
Mixed model assembly line literature involves two problems: balancing and model sequencing. The general tendency in current studies is to deal with these problems in different time frames. However, in today’s competitive market, the mixed model assembly line balancing problem has been turned into an...
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| Vydáno v: | Constraints : an international journal Ročník 18; číslo 3; s. 434 - 469 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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01.07.2013
Springer |
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| ISSN: | 1383-7133, 1572-9354 |
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| Abstract | Mixed model assembly line literature involves two problems: balancing and model sequencing. The general tendency in current studies is to deal with these problems in different time frames. However, in today’s competitive market, the mixed model assembly line balancing problem has been turned into an operational problem. In this paper, we propose mixed integer programming (MIP) and constraint programming (CP) models which consider both balancing and model sequencing within the same formulation along with the optimal schedule of tasks at a station. Furthermore, we also compare the proposed exact models with decomposition schemes developed for solving different instances of varying sizes. This is the first paper in the literature which takes into account the network type precedence diagrams and limited buffer capacities between stations. Besides, it is the first study that CP method is applied to balancing and scheduling of mixed model assembly lines. Our empirical study shows that the CP approach outperforms the MIP approach as well as the decomposition schemes. |
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| AbstractList | Mixed model assembly line literature involves two problems: balancing and model sequencing. The general tendency in current studies is to deal with these problems in different time frames. However, in today’s competitive market, the mixed model assembly line balancing problem has been turned into an operational problem. In this paper, we propose mixed integer programming (MIP) and constraint programming (CP) models which consider both balancing and model sequencing within the same formulation along with the optimal schedule of tasks at a station. Furthermore, we also compare the proposed exact models with decomposition schemes developed for solving different instances of varying sizes. This is the first paper in the literature which takes into account the network type precedence diagrams and limited buffer capacities between stations. Besides, it is the first study that CP method is applied to balancing and scheduling of mixed model assembly lines. Our empirical study shows that the CP approach outperforms the MIP approach as well as the decomposition schemes. |
| Author | Örnek, M. Arslan Hnich, Brahim Öztürk, Cemalettin Tunalı, Semra |
| Author_xml | – sequence: 1 givenname: Cemalettin surname: Öztürk fullname: Öztürk, Cemalettin organization: Department of Industrial Systems Engineering, İzmir University of Economics – sequence: 2 givenname: Semra surname: Tunalı fullname: Tunalı, Semra organization: Department of Business Administration, İzmir University of Economics – sequence: 3 givenname: Brahim surname: Hnich fullname: Hnich, Brahim email: hnich.brahim@gmail.com organization: Department of Computer Engineering, İzmir University of Economics – sequence: 4 givenname: M. Arslan surname: Örnek fullname: Örnek, M. Arslan organization: Department of Industrial Systems Engineering, İzmir University of Economics |
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| Issue | 3 |
| Keywords | Balancing Constraint programming Mixed integer programming Scheduling Decomposition Mixed model assembly lines Sequencing Assembly line Empirical method Constraint satisfaction Buffer system Modeling Constrained optimization Production management Economic market Product structure Flexible manufacturing system Capacity constraint Open market |
| Language | English |
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| SubjectTerms | Application Applied sciences Artificial Intelligence Computer Science Exact sciences and technology Firm modelling Inventory control, production control. Distribution Mathematical programming Operational research and scientific management Operational research. Management science Operations Research/Decision Theory Optimization Scheduling, sequencing |
| Title | Balancing and scheduling of flexible mixed model assembly lines |
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