A decomposition based solution algorithm for U-type assembly line balancing with interval data

Balancing U-type assembly lines under uncertainty is addressed in this research by formulating robust problem and developing an optimization model to design assembly lines that hedge against disruptions. U-type assembly layouts are shown to be more efficient than conventional straight lines. A great majority of the studies on these production systems assume deterministic environments and ignore uncertainty, such as the variations in operation times. We aim to fill this research gap and to the best of our knowledge, this study will be the first application of robust optimization to U-type assembly planning. We employ robust optimization that considers worst case situations. To avoid over-pessimism, we consider that only a subset of operation times take their worst case values. For solution, we apply an iterative approximate solution algorithm. The efficiency of the algorithm is evaluated with some computational tests.