Mixed model assembly line balancing problem under uncertainty

A common assumption in the literature on mixed model assembly line balancing problem is that the task duration is known and deterministic but may differ among various models. In this paper, we present a robust optimization formulation for dealing with task duration uncertainty in a mixed model assembly line balancing problem (RMALB-P) in which task duration can vary in a specific range. RMALB-P is aim to minimize the sum of costs of the stations and the task duplication. Task duplication means that a task which is common to multiple tasks can be assigned to different stations for different models. Finally, RMALB-P is solved optimally and implemented in mixed model assembly lines of IRAN KHODRO Company. The results are compared with the previous existing balance to show the effects of the data uncertainties on the performance of assembly line outputs. The results indicate that the robust balancing approach can be a relatively more reliable method for balancing the mixed model assembly lines.