Multi-objective multi-model assembly line balancing problem: a quantitative study in engine manufacturing industry
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This paper deals with multi-model assembly line balancing problem (MuMALBP). In multi-model assembly lines several products are produced in separate batches on a single assembly line. Despite their popular applications, these kinds of lines have been rarely studied in the literature. In this paper, a multi-objective mixed-integer linear programing model is proposed for balancing multi-model assembly lines. Three objectives are simultaneously considered in the proposed model. These are: (1) minimizing cycle time for each model (2) maximizing number of common tasks assigned to the same workstations, and (3) maximizing level of workload distribution smoothness between workstations. Performance of the proposed model is empirically investigated in a real world engine assembly line. After applying the proposed model, possible minimum cycle time is attained for each model. All common tasks are assigned to the same workstations and a highest possible level of workload distribution smoothness is achieved. It is shown that the best compromise solution has led to the best value of the first and second objective functions with a slight distance from the best value of third one.
KeywordsAssembly line balancing Multi-model assembly line Multi-objective optimization Mixed-integer linear programming Engine manufacturing industry
This work has been supported by the High Performance Computing Research Center (HPCRC)—Amirkabir University of Technology under the contract No ISI-DCE-DOD-Cloud-900808-1700.
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