Abstract
A line balancing problem is defined by a line along which vehicles go througth and are progressivly assembled. The assembly operations are performed by workstations spread along the line. The objective is to assign operations to workstations in order to minimize, for instance the number of required workstations. The basic constraints are cycle time and precedence constraints. To solve this problem, we have firstly used a genetic algorithm with different operators (some of them have been proposed in the literature). We suggest to couple this genetic algorithm with some heuristics (which have been previously published). We then obtain hybrid methods that improve the obtained offsprings, before inserting them in the population. We have tested these methods on literature instances (one range of vehicles and cycle time and precedence constraints), and on generated and industrial data. These real instances represent a real problem in the automotive industry.
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Boutevin, C., Deroussi, L., Gourgand, M., Norre, S. (2005). Hybrid Methods for Line Balancing Problems. In: Dolgui, A., Soldek, J., Zaikin, O. (eds) Supply Chain Optimisation. Applied Optimization, vol 94. Springer, Boston, MA. https://doi.org/10.1007/0-387-23581-7_9
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DOI: https://doi.org/10.1007/0-387-23581-7_9
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