In this study, an integrated bi-objective objective U-shaped assembly line balancing and parts feeding problem is explored by considering the heterogeneity inherent of workers. An optimization model is developed to formulate the addressed problem. Since the problem includes two different objectives, namely the minimizing the operational cost and maximum workload imbalance, the Pareto-optimal solutions are found by employing the second version of the augmented epsilon-constrained (AUGMECON2) method. To investigate the impact of qualification of workers on the system performance, a set of scenarios is constructed based on the worker skill levels. Each scenario is determined based on the nature of the worker pool in which workers are assigned to the stations. The optimization model and implemented method are validated through data taken from water-meter and elevator producers. The computational results reveal that the scenarios have a great impact on system performance. In particular, it is revealed that as the skill levels of workers increases, the quality of the Pareto-optimal solutions increase by up to 30% in terms of the comparison metrics. Therefore, an order release mechanism and worker training activities are suggested to be performed to enhance system performance.